Mum, why are the potholes 8 feet apart? Repetitive wheel loads from heavy vehicles in the spatial domain

This paper presents the results of testing to determine pavement forces from three heavy vehicles (HVs). The HVs were instrumented to measure their wheel forces. A “novel roughness” value of the roads during testing is also derived. The various dynamic pavement forces are presented according to the range of novel roughness of pavement surfacings encountered during testing. The paper then examines the relationship between the two derived wavelengths predominant within the HV suspensions; those of axle hop and body-bounce. How these may be considered as contributing to spatial repetition of pavement forces from HVs is discussed. The paper concludes that pavement models need to be revised since dynamic forces from HVs in particular are not generally considered in current pavement design.

Load-sharing in heavy vehicle suspensions : new metrics for old

Dynamic load sharing can be defined as a measure of the ability of a heavy vehicle multi-axle group to equalise load across its wheels under typical travel conditions; i.e. in the dynamic sense at typical travel speeds and operating conditions of that vehicle. Various attempts have been made to quantify the ability of heavy vehicles to equalise the load across their wheels during travel. One of these was the concept of the load sharing coefficient (LSC). Other metrics such as the dynamic load coefficient (DLC), peak dynamic wheel force (PDWF) and dynamic impact force (DIF) have been used to compare one heavy vehicle suspension with another for potential road damage. This paper compares these metrics and determines a relationship between DLC and LSC with sensitivity analysis of this relationship. The shortcomings of the presently-available metrics are discussed with a new metric proposed - the dynamic load equalisation (DLE) measure.

Development of a software model of a heavy vehicle suspension for research

A Simulink Matlab control system of a heavy vehicle suspension has been developed. The aim of the exercise presented in this paper was to develop a Simulink Matlab control system of a heavy vehicle suspension. The objective facilitated by this outcome was the use of a working model of a heavy vehicle (HV) suspension that could be used for future research. A working computer model is easier and cheaper to re-configure than a HV axle group installed on a truck; it presents less risk should something go wrong and allows more scope for variation and sensitivity analysis before embarking on further "real-world" testing. Empirical data recorded as the input and output signals of a heavy vehicle (HV) suspension were used to develop the parameters for computer simulation of a linear time invariant system described by a second-order differential equation of the form: (i.e. a "2nd-order" system). Using the empirical data as an input to the computer model allowed validation of its output compared with the empirical data. The errors ranged from less than 1% to approximately 3% for any parameter, when comparing like-for-like inputs and outputs. The model is presented along with the results of the validation. This model will be used in future research in the QUT/Main Roads project Heavy vehicle suspensions – testing and analysis, particularly so for a theoretical model of a multi-axle HV suspension with varying values of dynamic load sharing. Allowance will need to be made for the errors noted when using the computer models in this future work.

Size and habit of mineral particles in bone and mineralized callus during bone healing in sheep

Bone healing is known to occur through the successive formation and resorption of various tissues with different structural and mechanical properties. To get a better insight into this sequence of events, we used environmental scanning electron microscopy (ESEM) together with scanning small-angle X-ray scattering (sSAXS) to reveal the size and orientation of bone mineral particles within the regenerating callus tissues at different healing stages (2, 3, 6, and 9 weeks). Sections of 200 µm were cut from embedded blocks of midshaft tibial samples in a sheep osteotomy model with an external fixator. Regions of interest on the medial side of the proximal fragment were chosen to be the periosteal callus, middle callus, intercortical callus, and cortex. Mean thickness (T parameter), degree of alignment (ρ parameter), and predominant orientation (ψ parameter) of mineral particles were deduced from resulting sSAXS patterns with a spatial resolution of 200 µm. 2D maps of T and ρ overlapping with ESEM images revealed that the callus formation occurred in two waves of bone formation, whereby a highly disordered mineralized tissue was deposited first, followed by a bony tissue with more lamellar appearance in the ESEM and where the mineral particles were more aligned, as revealed by sSAXS. As a consequence, degree of alignment and mineral particle size within the callus increased with healing time, whereas at any given moment there were structural gradients, for example, from periosteal toward the middle callus.

Spatial and temporal variations of mechanical properties and mineral content of the external callus during bone healing

After bone fracture, various cellular activities lead to the formation of different tissue types, which form the basis for the process of secondary bone healing. Although these tissues have been quantified by histology, their material properties are not well understood. Thus, the aim of this study is to correlate the spatial and temporal variations in the mineral content and the nanoindentation modulus of the callus formed via intramembranous ossification over the course of bone healing. Midshaft tibial samples from a sheep osteotomy model at time points of 2, 3, 6 and 9 weeks were employed. PMMA embedded blocks were used for quantitative back scattered electron imaging and nanoindentation of the newly formed periosteal callus near the cortex. The resulting indentation modulus maps show the heterogeneity in the modulus in the selected regions of the callus. The indentation modulus of the embedded callus is about 6 GPa at the early stage. At later stages of mineralization, the average indentation modulus reaches 14 GPa. There is a slight decrease in average indentation modulus in regions distant to the cortex, probably due to remodelling of the peripheral callus. The spatial and temporal distribution of mineral content in the callus tissue also illustrates the ongoing remodelling process observed from histological analysis. Most interestingly the average indentation modulus, even at 9 weeks, remains as low as 13 GPa, which is roughly 60% of that for cortical sheep bone. The decreased indentation modulus in the callus compared to cortex is due to the lower average mineral content and may be perhaps also due to the properties of the organic matrix which might be different from normal bone.

Raman spectroscopic study of the uranyl titanate mineral brannerite (U,Ca,Y,Ce)2(Ti,Fe)2O6 –Effect of Metamictization

Raman spectra of the uranyl titanate mineral brannerite were analysed and related to the mineral structure. A comparison is made with the Raman spectra of uranyl oxyhydroxide hydrates. Observed bands are attributed to the TiO and (UO2)2+ stretching and bending vibrations, U-OH bending vibrations, H2O and (OH)- stretching, bending and libration modes. U-O bond lengths in uranyls and O-H…O bond lengths are calculated from the wavenumbers assigned to the stretching vibrations. Raman bands of brannerite are in harmony with those of the uranyl oxyhydroxides. The mineral brannerite is metamict as is evidenced by the intensity of the UO stretching and bending modes being of lower intensity than expected and with bands that are significantly broader.

Single crystal Raman spectroscopy of natural leiteite ZnAs2O4 and in comparison with the synthesised mineral

The oriented single crystal Raman spectrum of leiteite has been obtained and the spectra related to the structure of the mineral. The intensities of the observed bands vary according to orientation allowing them to be assigned to either Ag or Bg modes. Ag bands are generally the most intense in the CAAC spectrum, followed by ACCA, CBBC, and ABBA whereas Bg bands are generally the most intense in the CBAC followed by ABCA. The CAAC and ACCA spectra are identical, as are those obtained in the CBBC and ABBA orientations. Both cross-polarised spectra are identical. Band assignments were made with respect to bridging and non-bridging As-O bonds.

A crash avoidance framework for heavy equipment control systems using 3D imaging sensors

This paper presents a preliminary crash avoidance framework for heavy equipment control systems. Safe equipment operation is a major concern on construction sites since fatal on-site injuries are an industry-wide problem. The proposed framework has potential for effecting active safety for equipment operation. The framework contains algorithms for spatial modeling, object tracking, and path planning. Beyond generating spatial models in fractions of seconds, these algorithms can successfully track objects in an environment and produce a collision-free 3D motion trajectory for equipment.

Analysis of build-up of heavy metals and volatile organics on urban roads in Gold Coast, Australia

Urban water quality can be significantly impaired by the build-up of pollutants such as heavy metals and volatile organics on urban road surfaces due to vehicular traffic. Any control strategy for the mitigation of traffic related build-up of heavy metals and volatile organic pollutants should be based on the knowledge of their build-up processes. In the study discussed in this paper, the outcomes of a detailed experiment investigation into build-up processes of heavy metals and volatile organics are presented. It was found that traffic parameters such as average daily traffic, volume over capacity ratio and surface texture depth had similar strong correlations with the build-up of heavy metals and volatile organics. Multicriteria decision analyses revealed that the 1 - 74 um particulate fraction of total suspended solids (TSS) could be regarded as a surrogate indicator for particulate heavy metals in build-up and this same fraction of total organic carbon could be regarded as a surrogate indicator for particulate volatile organics build-up. In terms of pollutants affinity, TSS was found to be the predominant parameter for particulate heavy metals build-up and total dissolved solids was found to be the predominant parameter for he potential dissolved particulate fraction in heavy metals build-up. It was also found that land use did not play a significant role in the build-up of traffic generated heavy metals and volatile organics.

Raman spectroscopic study of the uranyl titanate mineral euxenite (Y,Ca,U,Ce,Th) (Nb,Ta,Ti)2O6

Raman spectra of the uranyl titanate mineral euxenite were analyzed and related to the mineral structure. A comparison is made with the Raman spectra of uranyl oxyhydroxide hydrates. The obsd. bands are attributed to the Ti[n.63743]O and (UO2)2+ stretching and bending vibrations, as well as lattice vibrations of rare-earth ions. The Raman bands of euxenite are in harmony with those of the uranyl oxyhydroxides. The mineral euxenite is metamict as is evidenced by the intensity of the U[n.63743]O stretching and bending modes, which are of lower intensity than expected, and with bands that are significantly broader.

Integrated Acquisition Engineering Model for acquiring heavy engineering assets

In asset intensive industries such as mining, oil & gas, utilities etc. most of the capital expenditure happens on acquiring engineering assets. Process of acquiring assets is called as “Procurement” or “Acquisition”. An asset procurement decision should be taken in consideration with the installation, commissioning, operational, maintenance and disposal needs of an asset or spare. However, such cross-functional collaboration and communication does not appear to happen between engineering, maintenance, warehousing and procurement functions in many asset intensive industries. Acquisition planning and execution are two distinct parts of asset acquisition process. Acquisition planning or procurement planning is responsible for determining exactly what is required to be purchased. It is important that an asset acquisition decision is the result of cross-functional decision making process. An acquisition decision leads to a formal purchase order. Most costly asset decisions occur even before they are acquired. Therefore, acquisition decision should be an outcome of an integrated planning & decision making process. Asset intensive organizations both, Government and non Government in Australia spent AUD 102.5 Billion on asset acquisition in year 2008-09. There is widespread evidence of many assets and spare not being used or utilized and in the end are written off. This clearly shows that many organizations end up buying assets or spares which were not required or non-conforming to the needs of user functions. It is due the fact that strategic and software driven procurement process do not consider all the requirements from various functions within the organization which contribute to the operation and maintenance of the asset over its life cycle. There is a lot of research done on how to implement an effective procurement process. There are numerous software solutions available for executing a procurement process. However, not much research is done on how to arrive at a cross functional procurement planning process. It is also important to link procurement planning process to procurement execution process. This research will discuss ““Acquisition Engineering Model” (AEM) framework, which aims at assisting acquisition decision making based on various criteria to satisfy cross-functional organizational requirements. Acquisition Engineering Model (AEM) will consider inputs from corporate asset management strategy, production management, maintenance management, warehousing, finance and HSE. Therefore, it is essential that the multi-criteria driven acquisition planning process is carried out and its output is fed to the asset acquisition (procurement execution) process. An effective procurement decision making framework to perform acquisition planning which considers various functional criteria will be discussed in this paper.

Vibrational spectroscopic study of the antimonate mineral bindheimite Pb2Sb2O6(O,OH)

Raman spectroscopy complimented with infrared spectroscopy has been used to characterise the antimonate mineral bindheimite Pb2Sb2O6(O,OH). The mineral is characterised by an intense Raman band at 656 cm-1 assigned to SbO stretching vibrations. Other lower intensity bands at 664, 749 and 814 cm-1 are also assigned to stretching vibrations. This observation suggests the non-equivalence of SbO units in the structure. Low intensity Raman bands at 293, 312 and 328 cm-1 are assigned to the OSbO bending vibrations. Infrared bands at 979, 1008, 1037 and 1058 cm-1 may be assigned to δ OH deformation modes of SbOH units. Infrared bands at 1603 and 1640 cm-1 are assigned to water bending vibrations, suggesting that water is involved in the bindheimite structure. Broad infrared bands centred upon 3250 cm-1 supports this concept. Thus the true formula of bindheimite is questioned and probably should be written as Pb2Sb2O6(O,OH,H2O)

A Raman spectroscopic study of the ‘cave’ mineral ardealite Ca2(HPO4)(SO4)•4H2O

The mineral ardealite Ca2(HPO4)(SO4)•4H2O is a ‘cave’ mineral and is formed through the reaction of calcite with bat guano. The mineral shows disorder and the composition varies depending on the origin of the mineral. Raman spectroscopy complimented with infrared spectroscopy has been used to characterise the mineral ardealite. The Raman spectrum is very different from that of gypsum. Bands are assigned to SO42- and HPO42- stretching and bending modes.

Thermal stability of the ‘cave’ mineral brushite CaHPO4•2H2O -mechanism of formation and decomposition

Thermogravimetry combined with evolved gas mass spectrometry has been used to ascertain the stability of the ‘cave’ mineral brushite. X-ray diffraction shows that brushite from the Jenolan Caves is very pure. Thermogravimetric analysis coupled with ion current mass spectrometry shows a mass loss at 111°C due to loss of water of hydration. A further decomposition step occurs at 190°C with the conversion of hydrogen phosphate to a mixture of calcium ortho-phosphate and calcium pyrophosphate. TG-DTG shows the mineral is not stable above 111°C. A mechanism for the formation of brushite on calcite surfaces is proposed, and this mechanism has relevance to the formation of brushite in urinary tracts.

The application of Raman spectroscopy to the study of the uranyl mineral coconinoite Fe2Al2(UO2)2(PO4)4(SO4)(OH)2•20H2O

Raman spectra of the uranyl containing mineral coconinoite, Fe2Al2(UO2)2(PO4)4(SO4)(OH)2•20H2O, are presented and compared with the mineral’s infrared spectra. Bands connected with (UO2)2+, (PO4)3- , (SO4)2-, (OH)- and H2O stretching and bending vibrations, are assigned. Approximate U-O bond lengths in uranyl, (UO2)2+, and O-H...O hydrogen bond lengths are calculated from the wavenumbers of the U-O stretching vibrations and (OH)- and H2O stretching vibrations, respectively, and compared with published data for similar natural and synthetic compounds.