962 resultados para Hybrid constraint methods


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This paper describes the use of a formal optimisation procedure to optimise a plug-in hybrid electric bus using two different case studies to meet two different performance criteria; minimum journey cost and maximum battery life. The approach is to choose a commercially available vehicle and seek to improve its performance by varying key design parameters. Central to this approach is the ability to develop a representative backward facing model of the vehicle in MATLAB/Simulink along with appropriate optimisation objective and penalty functions. The penalty functions being the margin by which a particular design fails to meet the performance specification. The model is validated against data collected from an actual vehicle and is used to estimate the vehicle performance parameters in a model-in-the-loop process within an optimisation routine. For the purposes of this paper, the journey cost/battery life over a drive cycle is optimised whilst other performance indices are met (or exceeded). Among the available optimisation methods, Powell's method and Simulated Annealing are adopted. The results show this method as a valid alternative modelling approach to vehicle powertrain optimisation. © 2012 IEEE.

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In this paper we propose a hybrid TCP/UDP transport, specifically for H.264/AVC encoded video, as a compromise between the delay-prone TCP and the loss-prone UDP. When implementing the hybrid approach, we argue that the playback at the receiver often need not be 100% perfect, provided that a certain level of quality is assured. Reliable TCP is used to transmit and guarantee delivery of the most important packets. This allows use of additional features in the H.264/AVC standard which simultaneously provide an enhanced playback quality, in addition to a reduction in throughput. These benefits are demonstrated through experimental results using a test-bed to emulate the hybrid proposal. We compare the proposed system with other protection methods, such as FEC, and in one case show that for the same bandwidth overhead, FEC is unable to match the performance of the hybrid system in terms of playback quality. Furthermore, we measure the delay associated with our approach, and examine its potential for use as an alternative to the conventional methods of transporting video by either TCP or UDP alone. © 2011 IEEE.

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This study describes an optimised modulation strategy based on switching state sequences for the hybrid-clamped multilevel converter. Two key control variables defined as 'phase shift angle' and 'switching state change' for a five-level hybrid-clamped inverter are proposed to improve all switches' operation, and by changing their values, different control methods can be obtained for modulation optimisation purposes. Two example methods can solve the voltage imbalance problem of the dc-link capacitors and furthermore avoid two switches' simultaneous switching transitions and improve the inverter's performance as compared with the traditional phase disposition pulse-width modulation strategy. A 6 kW prototype inverter is developed and a range of simulation and experiments are carried out for validation. It is found that simulation and experimental results are in a good agreement and the proposed modulation strategy is verified in terms of low-order harmonic reduction.

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As part of a multi-university research program funded by NSF, a comprehensive experimental and analytical study of seismic behavior of hybrid fiber reinforced polymer (FRP)-concrete column is presented in this dissertation. Experimental investigation includes cyclic tests of six large-scale concrete-filled FRP tube (CFFT) and RC columns followed by monotonic flexural tests, a nondestructive evaluation of damage using ultrasonic pulse velocity in between the two test sets and tension tests of sixty-five FRP coupons. Two analytical models using ANSYS and OpenSees were developed and favorably verified against both cyclic and monotonic flexural tests. The results of the two methods were compared. A parametric study was also carried out to investigate the effect of three main parameters on primary seismic response measures. The responses of typical CFFT columns to three representative earthquake records were also investigated. The study shows that only specimens with carbon FRP cracked, whereas specimens with glass or hybrid FRP did not show any visible cracks throughout cyclic tests. Further monotonic flexural tests showed that carbon specimens both experienced flexural cracks in tension and crumpling in compression. Glass or hybrid specimens, on the other hand, all showed local buckling of FRP tubes. Compared with conventional RC columns, CFFT column possesses higher flexural strength and energy dissipation with an extended plastic hinge region. Among all CFFT columns, the hybrid lay-up demonstrated the highest flexural strength and initial stiffness, mainly because of its high reinforcement index and FRP/concrete stiffness ratio, respectively. Moreover, at the same drift ratio, the hybrid lay-up was also considered as the best in term of energy dissipation. Specimens with glassfiber tubes, on the other hand, exhibited the highest ductility due to better flexibility of glass FRP composites. Furthermore, ductility of CFFTs showed a strong correlation with the rupture strain of FRP. Parametric study further showed that different FRP architecture and rebar types may lead to different failure modes for CFFT columns. Transient analysis of strong ground motions showed that the column with off-axis nonlinear filament-wound glass FRP tube exhibited a superior seismic performance to all other CFFTs. Moreover, higher FRP reinforcement ratios may lead to a brittle system failure, while a well-engineered FRP reinforcement configuration may significantly enhance the seismic performance of CFFT columns.

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The accurate and reliable estimation of travel time based on point detector data is needed to support Intelligent Transportation System (ITS) applications. It has been found that the quality of travel time estimation is a function of the method used in the estimation and varies for different traffic conditions. In this study, two hybrid on-line travel time estimation models, and their corresponding off-line methods, were developed to achieve better estimation performance under various traffic conditions, including recurrent congestion and incidents. The first model combines the Mid-Point method, which is a speed-based method, with a traffic flow-based method. The second model integrates two speed-based methods: the Mid-Point method and the Minimum Speed method. In both models, the switch between travel time estimation methods is based on the congestion level and queue status automatically identified by clustering analysis. During incident conditions with rapidly changing queue lengths, shock wave analysis-based refinements are applied for on-line estimation to capture the fast queue propagation and recovery. Travel time estimates obtained from existing speed-based methods, traffic flow-based methods, and the models developed were tested using both simulation and real-world data. The results indicate that all tested methods performed at an acceptable level during periods of low congestion. However, their performances vary with an increase in congestion. Comparisons with other estimation methods also show that the developed hybrid models perform well in all cases. Further comparisons between the on-line and off-line travel time estimation methods reveal that off-line methods perform significantly better only during fast-changing congested conditions, such as during incidents. The impacts of major influential factors on the performance of travel time estimation, including data preprocessing procedures, detector errors, detector spacing, frequency of travel time updates to traveler information devices, travel time link length, and posted travel time range, were investigated in this study. The results show that these factors have more significant impacts on the estimation accuracy and reliability under congested conditions than during uncongested conditions. For the incident conditions, the estimation quality improves with the use of a short rolling period for data smoothing, more accurate detector data, and frequent travel time updates.

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Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available protection concepts and devices for AC systems in a DC network, were presented. A study was also conducted on the effect of changing the distribution architecture and distributing the storage assets on the various zones of the network on the system's dynamic security and stability. A practical shipboard power system was studied as an example of a hybrid AC/DC power system involving pulsed loads. Generally, the proposed hybrid AC/DC power system, besides most of the ideas, controls and algorithms presented in this dissertation, were experimentally verified at the Smart Grid Testbed, Energy Systems Research Laboratory. All the developments in this dissertation were experimentally verified at the Smart Grid Testbed.

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As part of a multi-university research program funded by NSF, a comprehensive experimental and analytical study of seismic behavior of hybrid fiber reinforced polymer (FRP)-concrete column is presented in this dissertation. Experimental investigation includes cyclic tests of six large-scale concrete-filled FRP tube (CFFT) and RC columns followed by monotonic flexural tests, a nondestructive evaluation of damage using ultrasonic pulse velocity in between the two test sets and tension tests of sixty-five FRP coupons. Two analytical models using ANSYS and OpenSees were developed and favorably verified against both cyclic and monotonic flexural tests. The results of the two methods were compared. A parametric study was also carried out to investigate the effect of three main parameters on primary seismic response measures. The responses of typical CFFT columns to three representative earthquake records were also investigated. The study shows that only specimens with carbon FRP cracked, whereas specimens with glass or hybrid FRP did not show any visible cracks throughout cyclic tests. Further monotonic flexural tests showed that carbon specimens both experienced flexural cracks in tension and crumpling in compression. Glass or hybrid specimens, on the other hand, all showed local buckling of FRP tubes. Compared with conventional RC columns, CFFT column possesses higher flexural strength and energy dissipation with an extended plastic hinge region. Among all CFFT columns, the hybrid lay-up demonstrated the highest flexural strength and initial stiffness, mainly because of its high reinforcement index and FRP/concrete stiffness ratio, respectively. Moreover, at the same drift ratio, the hybrid lay-up was also considered as the best in term of energy dissipation. Specimens with glassfiber tubes, on the other hand, exhibited the highest ductility due to better flexibility of glass FRP composites. Furthermore, ductility of CFFTs showed a strong correlation with the rupture strain of FRP. Parametric study further showed that different FRP architecture and rebar types may lead to different failure modes for CFFT columns. Transient analysis of strong ground motions showed that the column with off-axis nonlinear filament-wound glass FRP tube exhibited a superior seismic performance to all other CFFTs. Moreover, higher FRP reinforcement ratios may lead to a brittle system failure, while a well-engineered FRP reinforcement configuration may significantly enhance the seismic performance of CFFT columns.

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This work applies a hybrid approach in solving the university curriculum-based course timetabling problem as presented as part of the 2nd International Timetabling Competition 2007 (ITC2007). The core of the hybrid approach is based on an artificial bee colony algorithm. Past methods have applied artificial bee colony algorithms to university timetabling problems with high degrees of success. Nevertheless, there exist inefficiencies in the associated search abilities in term of exploration and exploitation. To improve the search abilities, this work introduces a hybrid approach entitled nelder-mead great deluge artificial bee colony algorithm (NMGD-ABC) where it combined additional positive elements of particle swarm optimization and great deluge algorithm. In addition, nelder-mead local search is incorporated into the great deluge algorithm to further enhance the performance of the resulting method. The proposed method is tested on curriculum-based course timetabling as presented in the ITC2007. Experimental results reveal that the proposed method is capable of producing competitive results as compared with the other approaches described in literature

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Hybrid simulation is a technique that combines experimental and numerical testing and has been used for the last decades in the fields of aerospace, civil and mechanical engineering. During this time, most of the research has focused on developing algorithms and the necessary technology, including but not limited to, error minimisation techniques, phase lag compensation and faster hydraulic cylinders. However, one of the main shortcomings in hybrid simulation that has pre- vented its widespread use is the size of the numerical models and the effect that higher frequencies may have on the stability and accuracy of the simulation. The first chapter in this document provides an overview of the hybrid simulation method and the different hybrid simulation schemes, and the corresponding time integration algorithms, that are more commonly used in this field. The scope of this thesis is presented in more detail in chapter 2: a substructure algorithm, the Substep Force Feedback (Subfeed), is adapted in order to fulfil the necessary requirements in terms of speed. The effects of more complex models on the Subfeed are also studied in detail, and the improvements made are validated experimentally. Chapters 3 and 4 detail the methodologies that have been used in order to accomplish the objectives mentioned in the previous lines, listing the different cases of study and detailing the hardware and software used to experimentally validate them. The third chapter contains a brief introduction to a project, the DFG Subshake, whose data have been used as a starting point for the developments that are shown later in this thesis. The results obtained are presented in chapters 5 and 6, with the first of them focusing on purely numerical simulations while the second of them is more oriented towards a more practical application including experimental real-time hybrid simulation tests with large numerical models. Following the discussion of the developments in this thesis is a list of hardware and software requirements that have to be met in order to apply the methods described in this document, and they can be found in chapter 7. The last chapter, chapter 8, of this thesis focuses on conclusions and achievements extracted from the results, namely: the adaptation of the hybrid simulation algorithm Subfeed to be used in conjunction with large numerical models, the study of the effect of high frequencies on the substructure algorithm and experimental real-time hybrid simulation tests with vibrating subsystems using large numerical models and shake tables. A brief discussion of possible future research activities can be found in the concluding chapter.

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This keynote presentation will report some of our research work and experience on the development and applications of relevant methods, models, systems and simulation techniques in support of different types and various levels of decision making for business, management and engineering. In particular, the following topics will be covered. Modelling, multi-agent-based simulation and analysis of the allocation management of carbon dioxide emission permits in China (Nanfeng Liu & Shuliang Li Agent-based simulation of the dynamic evolution of enterprise carbon assets (Yin Zeng & Shuliang Li) A framework & system for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps: a big data perspective (Jin Xu, Zheng Li, Shuliang Li & Yanyan Zhang) Open innovation: intelligent model, social media & complex adaptive system simulation (Shuliang Li & Jim Zheng Li) A framework, model and software prototype for modelling and simulation for deshopping behaviour and how companies respond (Shawkat Rahman & Shuliang Li) Integrating multiple agents, simulation, knowledge bases and fuzzy logic for international marketing decision making (Shuliang Li & Jim Zheng Li) A Web-based hybrid intelligent system for combined conventional, digital, mobile, social media and mobile marketing strategy formulation (Shuliang Li & Jim Zheng Li) A hybrid intelligent model for Web & social media dynamics, and evolutionary and adaptive branding (Shuliang Li) A hybrid paradigm for modelling, simulation and analysis of brand virality in social media (Shuliang Li & Jim Zheng Li) Network configuration management: attack paradigms and architectures for computer network survivability (Tero Karvinen & Shuliang Li)

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This report studied the effect of crumb rubber in the asphalt mixture. The mixtures were also having limestone filler as a modifier. Mastic and mortar (mastic-fine aggregate system) mixture having different quantities of crumb rubber and limestone filler modifiers have been tested in order to find the best rutting resistance combination with an acceptable stiffness. The rheological tests on bituminous mastics and mortars have done in the laboratories in Nottingham Transport Engineering Centre (NTEC) and University of Bologna (DICAM). In the second chapter, an extensive literature review about the binders, additives, asphalt mixtures, various modelling and testing methods have been reviewed. In the third chapter, the physical and rheological properties of the binders have been investigated using both traditional devices and DSRs. The forth chapter is dedicated to finding the behaviour of the modified mastics (Binder-modifier system) with different combinations. Five different combinations of crumb rubber and limestone filler mastic tested with various methods using Dynamic Shear Rheometers. In the fifth chapter, in order to find the effect of the modifiers in the rheological properties of the complete asphalt mixture, the fine aggregates added to the same mastic combinations. In this phase, the behaviour of the system so-called mortar; binder, rubber, filler and fine aggregates) has been studied using the DSR device and the traditional tests. The results show that using fine crumb rubber reduces the thermo sensibility of the mastic (Binder Bitumen System) and improves its elasticity. Limestone filler in the other hand increases the mixture stiffness at high Frequencies. Another important outcome of this research was that the rheological properties of the mortars were following the same trend of the mastics, therefore study the rheological properties of the mastic gives an upright estimation of the mortar.

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Incidental findings on low-dose CT images obtained during hybrid imaging are an increasing phenomenon as CT technology advances. Understanding the diagnostic value of incidental findings along with the technical limitations is important when reporting image results and recommending follow-up, which may result in an additional radiation dose from further diagnostic imaging and an increase in patient anxiety. This study assessed lesions incidentally detected on CT images acquired for attenuation correction on two SPECT/CT systems. Methods: An anthropomorphic chest phantom containing simulated lesions of varying size and density was imaged on an Infinia Hawkeye 4 and a Symbia T6 using the low-dose CT settings applied for attenuation correction acquisitions in myocardial perfusion imaging. Twenty-two interpreters assessed 46 images from each SPECT/CT system (15 normal images and 31 abnormal images; 41 lesions). Data were evaluated using a jackknife alternative free-response receiver-operating-characteristic analysis (JAFROC). Results: JAFROC analysis showed a significant difference (P < 0.0001) in lesion detection, with the figures of merit being 0.599 (95% confidence interval, 0.568, 0.631) and 0.810 (95% confidence interval, 0.781, 0.839) for the Infinia Hawkeye 4 and Symbia T6, respectively. Lesion detection on the Infinia Hawkeye 4 was generally limited to larger, higher-density lesions. The Symbia T6 allowed improved detection rates for midsized lesions and some lower-density lesions. However, interpreters struggled to detect small (5 mm) lesions on both image sets, irrespective of density. Conclusion: Lesion detection is more reliable on low-dose CT images from the Symbia T6 than from the Infinia Hawkeye 4. This phantom-based study gives an indication of potential lesion detection in the clinical context as shown by two commonly used SPECT/CT systems, which may assist the clinician in determining whether further diagnostic imaging is justified.

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The analysis of steel and composite frames has traditionally been carried out by idealizing beam-to-column connections as either rigid or pinned. Although some advanced analysis methods have been proposed to account for semi-rigid connections, the performance of these methods strongly depends on the proper modeling of connection behavior. The primary challenge of modeling beam-to-column connections is their inelastic response and continuously varying stiffness, strength, and ductility. In this dissertation, two distinct approaches—mathematical models and informational models—are proposed to account for the complex hysteretic behavior of beam-to-column connections. The performance of the two approaches is examined and is then followed by a discussion of their merits and deficiencies. To capitalize on the merits of both mathematical and informational representations, a new approach, a hybrid modeling framework, is developed and demonstrated through modeling beam-to-column connections. Component-based modeling is a compromise spanning two extremes in the field of mathematical modeling: simplified global models and finite element models. In the component-based modeling of angle connections, the five critical components of excessive deformation are identified. Constitutive relationships of angles, column panel zones, and contact between angles and column flanges, are derived by using only material and geometric properties and theoretical mechanics considerations. Those of slip and bolt hole ovalization are simplified by empirically-suggested mathematical representation and expert opinions. A mathematical model is then assembled as a macro-element by combining rigid bars and springs that represent the constitutive relationship of components. Lastly, the moment-rotation curves of the mathematical models are compared with those of experimental tests. In the case of a top-and-seat angle connection with double web angles, a pinched hysteretic response is predicted quite well by complete mechanical models, which take advantage of only material and geometric properties. On the other hand, to exhibit the highly pinched behavior of a top-and-seat angle connection without web angles, a mathematical model requires components of slip and bolt hole ovalization, which are more amenable to informational modeling. An alternative method is informational modeling, which constitutes a fundamental shift from mathematical equations to data that contain the required information about underlying mechanics. The information is extracted from observed data and stored in neural networks. Two different training data sets, analytically-generated and experimental data, are tested to examine the performance of informational models. Both informational models show acceptable agreement with the moment-rotation curves of the experiments. Adding a degradation parameter improves the informational models when modeling highly pinched hysteretic behavior. However, informational models cannot represent the contribution of individual components and therefore do not provide an insight into the underlying mechanics of components. In this study, a new hybrid modeling framework is proposed. In the hybrid framework, a conventional mathematical model is complemented by the informational methods. The basic premise of the proposed hybrid methodology is that not all features of system response are amenable to mathematical modeling, hence considering informational alternatives. This may be because (i) the underlying theory is not available or not sufficiently developed, or (ii) the existing theory is too complex and therefore not suitable for modeling within building frame analysis. The role of informational methods is to model aspects that the mathematical model leaves out. Autoprogressive algorithm and self-learning simulation extract the missing aspects from a system response. In a hybrid framework, experimental data is an integral part of modeling, rather than being used strictly for validation processes. The potential of the hybrid methodology is illustrated through modeling complex hysteretic behavior of beam-to-column connections. Mechanics-based components of deformation such as angles, flange-plates, and column panel zone, are idealized to a mathematical model by using a complete mechanical approach. Although the mathematical model represents envelope curves in terms of initial stiffness and yielding strength, it is not capable of capturing the pinching effects. Pinching is caused mainly by separation between angles and column flanges as well as slip between angles/flange-plates and beam flanges. These components of deformation are suitable for informational modeling. Finally, the moment-rotation curves of the hybrid models are validated with those of the experimental tests. The comparison shows that the hybrid models are capable of representing the highly pinched hysteretic behavior of beam-to-column connections. In addition, the developed hybrid model is successfully used to predict the behavior of a newly-designed connection.

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With the increasing complexity of today's software, the software development process is becoming highly time and resource consuming. The increasing number of software configurations, input parameters, usage scenarios, supporting platforms, external dependencies, and versions plays an important role in expanding the costs of maintaining and repairing unforeseeable software faults. To repair software faults, developers spend considerable time in identifying the scenarios leading to those faults and root-causing the problems. While software debugging remains largely manual, it is not the case with software testing and verification. The goal of this research is to improve the software development process in general, and software debugging process in particular, by devising techniques and methods for automated software debugging, which leverage the advances in automatic test case generation and replay. In this research, novel algorithms are devised to discover faulty execution paths in programs by utilizing already existing software test cases, which can be either automatically or manually generated. The execution traces, or alternatively, the sequence covers of the failing test cases are extracted. Afterwards, commonalities between these test case sequence covers are extracted, processed, analyzed, and then presented to the developers in the form of subsequences that may be causing the fault. The hypothesis is that code sequences that are shared between a number of faulty test cases for the same reason resemble the faulty execution path, and hence, the search space for the faulty execution path can be narrowed down by using a large number of test cases. To achieve this goal, an efficient algorithm is implemented for finding common subsequences among a set of code sequence covers. Optimization techniques are devised to generate shorter and more logical sequence covers, and to select subsequences with high likelihood of containing the root cause among the set of all possible common subsequences. A hybrid static/dynamic analysis approach is designed to trace back the common subsequences from the end to the root cause. A debugging tool is created to enable developers to use the approach, and integrate it with an existing Integrated Development Environment. The tool is also integrated with the environment's program editors so that developers can benefit from both the tool suggestions, and their source code counterparts. Finally, a comparison between the developed approach and the state-of-the-art techniques shows that developers need only to inspect a small number of lines in order to find the root cause of the fault. Furthermore, experimental evaluation shows that the algorithm optimizations lead to better results in terms of both the algorithm running time and the output subsequence length.

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This study presents two novel methods for treating important environmental contaminants from two different wastewater streams. One process utilizes the kinetic advantages and reliability of ion exchanging clinoptilolite in combination with biological treatment to remove ammonium from municipal sewage. A second process, HAMBgR (Hybrid Adsorption Membrane Biological Reactor), combines both ion exchange resin and bacteria into a single reactor to treat perchlorate contaminated waters. Combining physicochemical adsorptive treatment with biological treatment can provide synergistic benefits to the overall removal processes. Ion exchange removal solves some of the common operational reliability limitations of biological treatment, like slow response to environmental changes and leaching. Biological activity can in turn help reduce the economic and environmental challenges of ion exchange processes, like regenerant cost and brine disposal. The second section of this study presents continuous flow column experiments, used to demonstrate the ability of clinoptilolite to remove wastewater ammonium, as well as the effectiveness of salt regeneration using highly concentrated sea salt solutions. The working capacity of clinoptilolite more than doubled over the first few loading cycles, while regeneration recovered more than 98% of ammonium. Using the regenerant brine for subsequent halotolerant algae growth allowed for its repeated use, which could lead to cost savings and production of valuable algal biomass. The algae were able to uptake all ammonium in solution, and the brine was able to be used again with no loss in regeneration efficiency. This process has significant advantages over conventional biological nitrification; shorter retention times, wider range of operational conditions, and higher quality effluent free of nitrate. Also, since the clinoptilolite is continually regenerated and the regenerant is rejuvenated by algae, overall input costs are expected to be low. The third section of this study introduces the HAMBgR process for the elimination of perchlorate and presents batch isotherm experiments and pilot reactor tests. Results showed that a variety of ion-exchange resins can be effectively and repeatedly regenerated biologically, and maintain an acceptable working capacity. The presence of an adsorbent in the HAMBgR process improved bioreactor performance during operational fluctuations by providing a physicochemical backup to the biological process. Pilot reactor tests showed that the HAMBgR process reduced effluent perchlorate spikes by up to 97% in comparison to a conventional membrane bio-reactor (MBR) that was subject to sudden changes in influent conditions. Also, the HAMBgR process stimulated biological activity and lead to higher biomass concentrations during increased contaminant loading conditions. Conventional MBR systems can be converted into HAMBgR’s at a low cost, easily justifiable by the realized benefits. The concepts employed in the HAMBgR process can be adapted to treat other target contaminants, not just perchlorate.