Visual route recognition with a handful of bits

In this paper we use a sequence-based visual localization algorithm to reveal surprising answers to the question, how much visual information is actually needed to conduct effective navigation? The algorithm actively searches for the best local image matches within a sliding window of short route segments or 'sub-routes', and matches sub-routes by searching for coherent sequences of local image matches. In contract to many existing techniques, the technique requires no pre-training or camera parameter calibration. We compare the algorithm's performance to the state-of-the-art FAB-MAP 2.0 algorithm on a 70 km benchmark dataset. Performance matches or exceeds the state of the art feature-based localization technique using images as small as 4 pixels, fields of view reduced by a factor of 250, and pixel bit depths reduced to 2 bits. We present further results demonstrating the system localizing in an office environment with near 100% precision using two 7 bit Lego light sensors, as well as using 16 and 32 pixel images from a motorbike race and a mountain rally car stage. By demonstrating how little image information is required to achieve localization along a route, we hope to stimulate future 'low fidelity' approaches to visual navigation that complement probabilistic feature-based techniques.

Towards robust night and day place recognition using visible and thermal imaging

The chief challenge facing persistent robotic navigation using vision sensors is the recognition of previously visited locations under different lighting and illumination conditions. The majority of successful approaches to outdoor robot navigation use active sensors such as LIDAR, but the associated weight and power draw of these systems makes them unsuitable for widespread deployment on mobile robots. In this paper we investigate methods to combine representations for visible and long-wave infrared (LWIR) thermal images with time information to combat the time-of-day-based limitations of each sensing modality. We calculate appearance-based match likelihoods using the state-of-the-art FAB-MAP [1] algorithm to analyse loop closure detection reliability across different times of day. We present preliminary results on a dataset of 10 successive traverses of a combined urban-parkland environment, recorded in 2-hour intervals from before dawn to after dusk. Improved location recognition throughout an entire day is demonstrated using the combined system compared with methods which use visible or thermal sensing alone.

Assessment of flood-related recharge to alluvial aquifers of an irrigated catchment following extended drought conditions using 3D visualisation and environmental tracers, Lockyer Valley, southeast Queensland, Australia.

The Lockyer Valley in southeast Queensland, Australia, hosts an economically significant alluvial aquifer system which has been impacted by prolonged drought conditions (~1997 to ~ 2009). Throughout this time, the system was under continued groundwater extraction, resulting in severe aquifer depletion. By 2008, much of the aquifer was at <30% of storage but some relief occurred with rains in early 2009. However, between December 2010 and January 2011, most of southeast Queensland experienced unprecedented flooding, which generated significant aquifer recharge. In order to understand the spatial and temporal controls of groundwater recharge in the alluvium, a detailed 3D lithological property model of gravels, sands and clays was developed using GOCAD software. The spatial distribution of recharge throughout the catchment was assessed using hydrograph data from about 400 groundwater observation wells screened at the base of the alluvium. Water levels from these bores were integrated into a catchment-wide 3D geological model using the 3D geological modelling software GOCAD; the model highlights the complexity of recharge mechanisms. To support this analysis, groundwater tracers (e.g. major and minor ions, stable isotopes, 3H and 14C) were used as independent verification. The use of these complementary methods has allowed the identification of zones where alluvial recharge primarily occurs from stream water during episodic flood events. However, the study also demonstrates that in some sections of the alluvium, rainfall recharge and discharge from the underlying basement into the alluvium are the primary recharge mechanisms of the alluvium. This is indicated by the absence of any response to the flood, as well as the observed old radiocarbon ages and distinct basement water chemistry signatures at these locations. Within the 3D geological model, integration of water chemistry and time-series displays of water level surfaces before and after the flood suggests that the spatial variations of the flood response in the alluvium are primarily controlled by the valley morphology and lithological variations within the alluvium. The integration of time-series of groundwater level surfaces in the 3D geological model also enables the quantification of the volumetric change of groundwater stored in the unconfined sections of this alluvial aquifer during drought and following flood events. The 3D representation and analysis of hydraulic and recharge information has considerable advantages over the traditional 2D approach. For example, while many studies focus on singular aspects of catchment dynamics and groundwater-surface water interactions, the 3D approach is capable of integrating multiple types of information (topography, geological, hydraulic, water chemistry and spatial) into a single representation which provides valuable insights into the major factors controlling aquifer processes.

The 3D kinematics of the single leg flat and decline squat

Background: Pre-participation screening is commonly used to measure and assess potential intrinsic injury risk. The single leg squat is one such clinical screening measure used to assess lumbopelvic stability and associated intrinsic injury risk. With the addition of a decline board, the single leg decline squat (SLDS) has been shown to reduce ankle dorsiflexion restrictions and allowed greater sagittal plane movement of the hip and knee. On this basis, the SLDS has been employed in the Cricket Australia physiotherapy screening protocols as a measure of lumbopelvic control in the place of the more traditional single leg flat squat (SLFS). Previous research has failed to demonstrate which squatting technique allows for a more comprehensive assessment of lumbopelvic stability. Tenuous links are drawn between kinematics and hip strength measures within the literature for the SLS. Formal evaluation of subjective screening methods has also been suggested within the literature. Purpose: This study had several focal points namely 1) to compare the kinematic differences between the two single leg squatting conditions, primarily the five key kinematic variables fundamental to subjectively assess lumbopelvic stability; 2) determine the effect of ankle dorsiflexion range of motion has on squat kinematics in the two squat techniques; 3) examine the association between key kinematics and subjective physiotherapists’ assessment; and finally 4) explore the association between key kinematics and hip strength. Methods: Nineteen (n=19) subjects performed five SLDS and five SLFS on each leg while being filmed by an 8 camera motion analysis system. Four hip strength measures (internal/external rotation and abd/adduction) and ankle dorsiflexion range of motion were measured using a hand held dynamometer and a goniometer respectively on 16 of these subjects. The same 16 participants were subjectively assessed by an experienced physiotherapist for lumbopelvic stability. Paired samples t-tests were performed on the five predetermined kinematic variables to assess the differences between squat conditions. A Bonferroni correction for multiple comparisons was used which adjusted the significance value to p = 0.005 for the paired t-tests. Linear regressions were used to assess the relationship between kinematics, ankle range of motion and hip strength measures. Bivariate correlations between hip strength measures and kinematics and pelvic obliquity were employed to investigate any possible relationships. Results: 1) Significant kinematic differences between squats were observed in dominant (D) and non-dominant (ND) end of range hip external rotation (ND p = <0.001; D p = 0.004) and hip adduction kinematics (ND p = <0.001; D p = <0.001). With the mean angle, only the non-dominant leg observed significant differences in hip adduction (p = 0.001) and hip external rotation (p = <0.001); 2) Significant linear relationships were observed between clinical measures of ankle dorsiflexion and sagittal plane kinematic namely SLFS dominant ankle (p = 0.006; R2 = .429), SLFS non-dominant knee (p = 0.015; R2 = .352) and SLFS non-dominant ankle (p = 0.027; R2 = .305) kinematics. Only the dominant ankle (p = 0.020; R2 = .331) was found to have a relationship with the decline squat. 3) Strength measures had tenuous associations with the subjective assessments of lumbopelvic stability with no significant relationships being observed. 4) For the non-dominant leg, external rotation strength and abduction strength were found to be significantly correlated with hip rotation kinematics (Newtons r = 0.458 p = 0.049; Normalised for bodyweight: r = 0.469; p = 0.043) and pelvic obliquity (normalised for bodyweight: r = 0.498 p = 0.030) respectively for the SLFS only. No significant relationships were observed in the dominant leg for either squat condition. Some elements of the hip strength screening protocols had linear relationships with kinematics of the lower limb, particularly the sagittal plane movements of the knee and ankle. Strength measures had tenuous associations with the subjective assessments of lumbopelvic stability with no significant relationships being observed; Discussion: The key finding of this study illustrated that kinematic differences can occur at the hip without significant kinematic differences at the knee as a result of the introduction of a decline board. Further observations reinforce the role of limited ankle dorsiflexion range of motion on sagittal plane movement of the hip and knee and in turn multiplanar kinematics of the lower limb. The kinematic differences between conditions have clinical implications for screening protocols that employ frontal plane movement of the knee as a guide for femoral adduction and rotation. Subjects who returned stronger hip strength measurements also appeared to squat deeper as characterised by differences in sagittal plane kinematics of the knee and ankle. Despite the aforementioned findings, the relationship between hip strength and lower limb kinematics remains largely tenuous in the assessment of the lumbopelvic stability using the SLS. The association between kinematics and the subjective measures of lumbopelvic stability also remain tenuous between and within SLS screening protocols. More functional measures of hip strength are needed to further investigate these relationships. Conclusion: The type of SLS (flat or decline) should be taken into account when screening for lumbopelvic stability. Changes to lower limb kinematics, especially around the hip and pelvis, were observed with the introduction of a decline board despite no difference in frontal plane knee movements. Differences in passive ankle dorsiflexion range of motion yielded variations in knee and ankle kinematics during a self-selected single leg squatting task. Clinical implications of removing posterior ankle restraints and using the knee as a guide to illustrate changes at the hip may result in inaccurate screening of lumbopelvic stability. The relationship between sagittal plane lower limb kinematics and hip strength may illustrate that self-selected squat depth may presumably be a useful predictor of the lumbopelvic stability. Further research in this area is required.

Towards spontaneous facial expression recognition in real-world video

Facial expression is an important channel of human social communication. Facial expression recognition (FER) aims to perceive and understand emotional states of humans based on information in the face. Building robust and high performance FER systems that can work in real-world video is still a challenging task, due to the various unpredictable facial variations and complicated exterior environmental conditions, as well as the difficulty of choosing a suitable type of feature descriptor for extracting discriminative facial information. Facial variations caused by factors such as pose, age, gender, race and occlusion, can exert profound influence on the robustness, while a suitable feature descriptor largely determines the performance. Most present attention on FER has been paid to addressing variations in pose and illumination. No approach has been reported on handling face localization errors and relatively few on overcoming facial occlusions, although the significant impact of these two variations on the performance has been proved and highlighted in many previous studies. Many texture and geometric features have been previously proposed for FER. However, few comparison studies have been conducted to explore the performance differences between different features and examine the performance improvement arisen from fusion of texture and geometry, especially on data with spontaneous emotions. The majority of existing approaches are evaluated on databases with posed or induced facial expressions collected in laboratory environments, whereas little attention has been paid on recognizing naturalistic facial expressions on real-world data. This thesis investigates techniques for building robust and high performance FER systems based on a number of established feature sets. It comprises of contributions towards three main objectives: (1) Robustness to face localization errors and facial occlusions. An approach is proposed to handle face localization errors and facial occlusions using Gabor based templates. Template extraction algorithms are designed to collect a pool of local template features and template matching is then performed to covert these templates into distances, which are robust to localization errors and occlusions. (2) Improvement of performance through feature comparison, selection and fusion. A comparative framework is presented to compare the performance between different features and different feature selection algorithms, and examine the performance improvement arising from fusion of texture and geometry. The framework is evaluated for both discrete and dimensional expression recognition on spontaneous data. (3) Evaluation of performance in the context of real-world applications. A system is selected and applied into discriminating posed versus spontaneous expressions and recognizing naturalistic facial expressions. A database is collected from real-world recordings and is used to explore feature differences between standard database images and real-world images, as well as between real-world images and real-world video frames. The performance evaluations are based on the JAFFE, CK, Feedtum, NVIE, Semaine and self-collected QUT databases. The results demonstrate high robustness of the proposed approach to the simulated localization errors and occlusions. Texture and geometry have different contributions to the performance of discrete and dimensional expression recognition, as well as posed versus spontaneous emotion discrimination. These investigations provide useful insights into enhancing robustness and achieving high performance of FER systems, and putting them into real-world applications.

Integrated health prediction of bridge systems using dynamic object oriented Bayesian networks (DOOBNS)

The serviceability and safety of bridges are crucial to people’s daily lives and to the national economy. Every effort should be taken to make sure that bridges function safely and properly as any damage or fault during the service life can lead to transport paralysis, catastrophic loss of property or even casualties. Nonetheless, aggressive environmental conditions, ever-increasing and changing traffic loads and aging can all contribute to bridge deterioration. With often constrained budget, it is of significance to identify bridges and bridge elements that should be given higher priority for maintenance, rehabilitation or replacement, and to select optimal strategy. Bridge health prediction is an essential underpinning science to bridge maintenance optimization, since the effectiveness of optimal maintenance decision is largely dependent on the forecasting accuracy of bridge health performance. The current approaches for bridge health prediction can be categorised into two groups: condition ratings based and structural reliability based. A comprehensive literature review has revealed the following limitations of the current modelling approaches: (1) it is not evident in literature to date that any integrated approaches exist for modelling both serviceability and safety aspects so that both performance criteria can be evaluated coherently; (2) complex system modelling approaches have not been successfully applied to bridge deterioration modelling though a bridge is a complex system composed of many inter-related bridge elements; (3) multiple bridge deterioration factors, such as deterioration dependencies among different bridge elements, observed information, maintenance actions and environmental effects have not been considered jointly; (4) the existing approaches are lacking in Bayesian updating ability to incorporate a variety of event information; (5) the assumption of series and/or parallel relationship for bridge level reliability is always held in all structural reliability estimation of bridge systems. To address the deficiencies listed above, this research proposes three novel models based on the Dynamic Object Oriented Bayesian Networks (DOOBNs) approach. Model I aims to address bridge deterioration in serviceability using condition ratings as the health index. The bridge deterioration is represented in a hierarchical relationship, in accordance with the physical structure, so that the contribution of each bridge element to bridge deterioration can be tracked. A discrete-time Markov process is employed to model deterioration of bridge elements over time. In Model II, bridge deterioration in terms of safety is addressed. The structural reliability of bridge systems is estimated from bridge elements to the entire bridge. By means of conditional probability tables (CPTs), not only series-parallel relationship but also complex probabilistic relationship in bridge systems can be effectively modelled. The structural reliability of each bridge element is evaluated from its limit state functions, considering the probability distributions of resistance and applied load. Both Models I and II are designed in three steps: modelling consideration, DOOBN development and parameters estimation. Model III integrates Models I and II to address bridge health performance in both serviceability and safety aspects jointly. The modelling of bridge ratings is modified so that every basic modelling unit denotes one physical bridge element. According to the specific materials used, the integration of condition ratings and structural reliability is implemented through critical failure modes. Three case studies have been conducted to validate the proposed models, respectively. Carefully selected data and knowledge from bridge experts, the National Bridge Inventory (NBI) and existing literature were utilised for model validation. In addition, event information was generated using simulation to demonstrate the Bayesian updating ability of the proposed models. The prediction results of condition ratings and structural reliability were presented and interpreted for basic bridge elements and the whole bridge system. The results obtained from Model II were compared with the ones obtained from traditional structural reliability methods. Overall, the prediction results demonstrate the feasibility of the proposed modelling approach for bridge health prediction and underpin the assertion that the three models can be used separately or integrated and are more effective than the current bridge deterioration modelling approaches. The primary contribution of this work is to enhance the knowledge in the field of bridge health prediction, where more comprehensive health performance in both serviceability and safety aspects are addressed jointly. The proposed models, characterised by probabilistic representation of bridge deterioration in hierarchical ways, demonstrated the effectiveness and pledge of DOOBNs approach to bridge health management. Additionally, the proposed models have significant potential for bridge maintenance optimization. Working together with advanced monitoring and inspection techniques, and a comprehensive bridge inventory, the proposed models can be used by bridge practitioners to achieve increased serviceability and safety as well as maintenance cost effectiveness.

The effect of implementing a modified early warning scoring (MEWS) system on the adequacy of vital sign documentation

Introduction and objectives Early recognition of deteriorating patients results in better patient outcomes. Modified early warning scores (MEWS) attempt to identify deteriorating patients early so timely interventions can occur thus reducing serious adverse events. We compared frequencies of vital sign recording 24 h post-ICU discharge and 24 h preceding unplanned ICU admission before and after a new observation chart using MEWS and an associated educational programme was implemented into an Australian Tertiary referral hospital in Brisbane. Design Prospective before-and-after intervention study, using a convenience sample of ICU patients who have been discharged to the hospital wards, and in patients with an unplanned ICU admission, during November 2009 (before implementation; n = 69) and February 2010 (after implementation; n = 70). Main outcome measures Any change in a full set or individual vital sign frequency before-and-after the new MEWS observation chart and associated education programme was implemented. A full set of vital signs included Blood pressure (BP), heart rate (HR), temperature (T°), oxygen saturation (SaO2) respiratory rate (RR) and urine output (UO). Results After the MEWS observation chart implementation, we identified a statistically significant increase (210%) in overall frequency of full vital sign set documentation during the first 24 h post-ICU discharge (95% CI 148, 288%, p value <0.001). Frequency of all individual vital sign recordings increased after the MEWS observation chart was implemented. In particular, T° recordings increased by 26% (95% CI 8, 46%, p value = 0.003). An increased frequency of full vital sign set recordings for unplanned ICU admissions were found (44%, 95% CI 2, 102%, p value = 0.035). The only statistically significant improvement in individual vital sign recordings was urine output, demonstrating a 27% increase (95% CI 3, 57%, p value = 0.029). Conclusions The implementation of a new MEWS observation chart plus a supporting educational programme was associated with statistically significant increases in frequency of combined and individual vital sign set recordings during the first 24 h post-ICU discharge. There were no significant changes to frequency of individual vital sign recordings in unplanned admissions to ICU after the MEWS observation chart was implemented, except for urine output. Overall increases in the frequency of full vital sign sets were seen.

Temporal boundary objects in megaprojects : mapping the system with the integrated master schedule

Recently, a stream of project management research has recognized the critical role of boundary objects in the organization of projects. In this paper, we investigate how one advanced scheduling tool, the Integrated Master Schedule (IMS), is used as a temporal boundary object at various stages of complex projects. The IMS is critical to megaprojects which typically span long periods of time and face a high degree of complexity and uncertainty. In this paper, we conceptualize projects of this type as complex adaptive systems (CAS). We report the findings of four case projects on how the IMS mapped interactions, interdependencies, constraints, and fractal patterns of these emerging projects, and how the process of IMS visualization enabled communication and negotiation of project realities. This paper highlights that this advanced timeline tool acts as a boundary object and elicits shared understanding of complex projects from their stakeholders.

Emergence and the art system ‘plus minus now’

Emergence is discussed in the context of a practice-based study of interactive art and a new taxonomy of emergence is proposed. The interactive art system ‘plus minus now’ is described and its relationship to emergence is discussed. ‘Plus minus now’ uses a novel method for instantiating emergent shapes. A preliminary investigation of this art system has been conducted and reveals the creation of temporal compositions by a participant. These temporal compositions and the emergent shapes are described using the taxonomy of emergence. Characteristics of emergent interactions and the implications of designing for them are discussed.

JFA based Speaker Recognition using Delta-Phase and MFCC features

This paper investigates the use of mel-frequency deltaphase (MFDP) features in comparison to, and in fusion with, traditional mel-frequency cepstral coefficient (MFCC) features within joint factor analysis (JFA) speaker verification. MFCC features, commonly used in speaker recognition systems, are derived purely from the magnitude spectrum, with the phase spectrum completely discarded. In this paper, we investigate if features derived from the phase spectrum can provide additional speaker discriminant information to the traditional MFCC approach in a JFA based speaker verification system. Results are presented which provide a comparison of MFCC-only, MFDPonly and score fusion of the two approaches within a JFA speaker verification approach. Based upon the results presented using the NIST 2008 Speaker Recognition Evaluation (SRE) dataset, we believe that, while MFDP features alone cannot compete with MFCC features, MFDP can provide complementary information that result in improved speaker verification performance when both approaches are combined in score fusion, particularly in the case of shorter utterances.

The backfilled GEI : a cross-capture modality gait feature for frontal and side-view gait recognition

In this paper, we propose a novel direction for gait recognition research by proposing a new capture-modality independent, appearance-based feature which we call the Back-filled Gait Energy Image (BGEI). It can can be constructed from both frontal depth images, as well as the more commonly used side-view silhouettes, allowing the feature to be applied across these two differing capturing systems using the same enrolled database. To evaluate this new feature, a frontally captured depth-based gait dataset was created containing 37 unique subjects, a subset of which also contained sequences captured from the side. The results demonstrate that the BGEI can effectively be used to identify subjects through their gait across these two differing input devices, achieving rank-1 match rate of 100%, in our experiments. We also compare the BGEI against the GEI and GEV in their respective domains, using the CASIA dataset and our depth dataset, showing that it compares favourably against them. The experiments conducted were performed using a sparse representation based classifier with a locally discriminating input feature space, which show significant improvement in performance over other classifiers used in gait recognition literature, achieving state of the art results with the GEI on the CASIA dataset.

A waste management system for small and medium enterprises engaged in office building retrofit projects

Waste management and minimisation is considered to be an important issue for achieving sustainability in the construction industry. Retrofit projects generate less waste than demolitions and new builds, but they possess unique features and require waste management approaches that are different to traditional new builds. With the increasing demand for more energy efficient and environmentally sustainable office spaces, the office building retrofit market is growing in capital cities around Australia with a high level of refurbishment needed for existing aging properties. Restricted site space and uncertain delivery process in these projects make it a major challenge to manage waste effectively. The labour-intensive nature of retrofit projects creates the need for the involvement of small and medium enterprises (SMEs) as subcontractors in on-site works. SMEs are familiar with on-site waste generation but are not as actively motivated and engaged in waste management activities as the stakeholders in other construction projects in the industry. SMEs’ responsibilities for waste management in office building retrofit projects need to be identified and adapted to the work delivery processes and the waste management system supported by project stakeholders. The existing literature provides an understanding of how to manage construction waste that is already generated and how to increase the waste recovery rate for office building retrofit projects. However, previous research has not developed theories or practical solutions that can guide project stakeholders to understand the specific waste generation process and effectively plan for and manage waste in ongoing project works. No appropriate method has been established for the potential role and capability of SMEs to manage and minimise waste from their subcontracting works. This research probes into the characteristics of office building retrofit project delivery with the aim to develop specific tools to manage waste and incorporate SMEs in this process in an appropriate and effective way. Based on an extensive literature review, the research firstly developed a questionnaire survey to identify the critical factors of on-site waste generation in office building retrofit projects. Semi-structured interviews were then utilised to validate the critical waste factors and establish the interrelationships between the factors. The interviews served another important function of identifying the current problems of waste management in the industry and the performance of SMEs in this area. Interviewees’ opinions on remedies to the problems were also collected. On the foundation of the findings from the questionnaire survey and semi-structured interviews, two waste planning and management strategies were identified for the dismantling phase and fit-out phase of office building retrofit projects, respectively. Two models were then established to organize SMEs’ waste management activities, including a work process-based integrated waste planning model for the dismantling phase and a system dynamics model for the fit-out phase. In order to apply the models in real practice, procedures were developed to guide SMEs’ work flow in on-site waste planning and management. In addition, a collaboration framework was established for SMEs and other project stakeholders for effective waste planning and management. Furthermore, an organisational engagement strategy was developed to improve SME waste management practices. Three case studies were conducted to validate and finalise the research deliverables. This research extends the current literature that mostly covers waste management plans in new build projects, by presenting the knowledge and understanding of addressing waste problems in retrofit projects. It provides practical tools and guidance for industry practitioners to effectively manage the waste generation processes in office building retrofit projects. It can also promote industry-level recognition of the role of SMEs and their performance in on-site waste management.

The development of a Monte Carlo system to verify radiotherapy treatment dose calculations

Recent advances in the planning and delivery of radiotherapy treatments have resulted in improvements in the accuracy and precision with which therapeutic radiation can be administered. As the complexity of the treatments increases it becomes more difficult to predict the dose distribution in the patient accurately. Monte Carlo methods have the potential to improve the accuracy of the dose calculations and are increasingly being recognised as the “gold standard” for predicting dose deposition in the patient. In this study, software has been developed that enables the transfer of treatment plan information from the treatment planning system to a Monte Carlo dose calculation engine. A database of commissioned linear accelerator models (Elekta Precise and Varian 2100CD at various energies) has been developed using the EGSnrc/BEAMnrc Monte Carlo suite. Planned beam descriptions and CT images can be exported from the treatment planning system using the DICOM framework. The information in these files is combined with an appropriate linear accelerator model to allow the accurate calculation of the radiation field incident on a modelled patient geometry. The Monte Carlo dose calculation results are combined according to the monitor units specified in the exported plan. The result is a 3D dose distribution that could be used to verify treatment planning system calculations. The software, MCDTK (Monte Carlo Dicom ToolKit), has been developed in the Java programming language and produces BEAMnrc and DOSXYZnrc input files, ready for submission on a high-performance computing cluster. The code has been tested with the Eclipse (Varian Medical Systems), Oncentra MasterPlan (Nucletron B.V.) and Pinnacle3 (Philips Medical Systems) planning systems. In this study the software was validated against measurements in homogenous and heterogeneous phantoms. Monte Carlo models are commissioned through comparison with quality assurance measurements made using a large square field incident on a homogenous volume of water. This study aims to provide a valuable confirmation that Monte Carlo calculations match experimental measurements for complex fields and heterogeneous media.

Visualization of thermal characteristics around the absorber tube of a standard parabolic trough thermal collector by 3D simulation

Three dimensional conjugate heat transfer simulation of a standard parabolic trough thermal collector receiver is performed numerically in order to visualize and analyze the surface thermal characteristics. The computational model is developed in Ansys Fluent environment based on some simplified assumptions. Three test conditions are selected from the existing literature to verify the numerical model directly, and reasonably good agreement between the model and the test results confirms the reliability of the simulation. Solar radiation flux profile around the tube is also approximated from the literature. An in house macro is written to read the input solar flux as a heat flux wall boundary condition for the tube wall. The numerical results show that there is an abrupt variation in the resultant heat flux along the circumference of the receiver. Consequently, the temperature varies throughout the tube surface. The lower half of the horizontal receiver enjoys the maximum solar flux, and therefore, experiences the maximum temperature rise compared to the upper part with almost leveled temperature. Reasonable attributions and suggestions are made on this particular type of conjugate thermal system. The knowledge that gained so far from this study will be used to further the analysis and to design an efficient concentrator photovoltaic collector in near future.