Meeting the longevity requirements of solid-state lighting (SSL) devices places extreme demands on the materials and designs that are used in SSL luminaires. Therefore, understanding the aging characteristics of lens, reflectors, and other materials is essential to projecting the long-term performance of LED-based lighting systems. Overlooking these factors at either the design or product specification stage can result in premature failure of the device due to poor luminous flux maintenance and/or excessive chromaticity shifts. This paper describes a methodology for performing accelerated stress testing (AST) on materials intended for use in SSL luminaires. This test methodology, which consists of elevated temperature and humidity conditions, produces accelerated aging data that can be correlated to expected performance under normal luminaire operating conditions. The correlations can then be leveraged to produce models of the changes in the optical properties of key materials including transmittance versus wavelength of lenses and reflectance versus wavelength for housings and other reflectors. This information has been collected into a lumen maintenance decision support tool (LM-DST) and together with user supplied inputs (e.g., expected operation conditions) can provide guidance on lifetime expectations of SSL luminaires. This approach has been applied to a variety of materials commonly found in SSL luminaires including acrylics, polycarbonates, and silicones used for lenses and paints, coatings, films, and composites used for reflectors.

We present a heuristic control theory model that describes smoking under restricted and unrestricted access to cigarettes. The model is based on the allostasis theory and uses a formal representation of a multiscale opponent process. The model simulates smoking behavior of an individual and produces both short-term ("loading up" after not smoking for a while) and long-term smoking patterns (e.g., gradual transition from a few cigarettes to one pack a day). By introducing a formal representation of withdrawal- and craving-like processes, the model produces gradual increases over time in withdrawal- and craving-like signals associated with abstinence and shows that after 3 months of abstinence, craving disappears. The model was programmed as a computer application allowing users to select simulation scenarios. The application links images of brain regions that are activated during the binge/intoxication, withdrawal, or craving with corresponding simulated states. The model was calibrated to represent smoking patterns described in peer-reviewed literature; however, it is generic enough to be adapted to other drugs, including cocaine and opioids. Although the model does not mechanistically describe specific neurobiological processes, it can be useful in prevention and treatment practices as an illustration of drug-using behaviors and expected dynamics of withdrawal and craving during abstinence.

In rural areas availability, price, and legal consequences can force some drug users to switch be tw en primary drugs of choice. For example, as a conseque nce of stricter law enforcement policy in rural Ohio we observed a shift from methamphetamine use to heroin and prescr iption opiate use. We propose a polydrug agent-based model that describes drug users interconnected in a network. B ehavior rules are based on our ethnographic research. The d rug selection mechanisms are dictated by drug liking, d rug availability, drug cost, perception of health and other life consequences, perception of potential punishment an d pressure from the peers. The model produces time series of u sers’ choices of one or concurrent drugs. Modeling and ethnographic data collection are interlinked i.e. model results lead to the improvements in quantitative measuremen ts, which in turn improve the model. Polydrug trends are of particular interest to policy makers because short-term interv entions can lead to long-term adaptation. Keywordsdecision making, drug use modeling, drug switch, agent-based model, model-based survey

Results from accelerated life tests (ALT) on mass-produced commercially available 6" downlights are reported along with results from commercial LEDs. The luminaires capture many of the design features found in modern luminaires. In general, a systems perspective is required to understand the reliability of these devices since LED failure is rare. In contrast, components such as drivers, lenses, and reflector are more likely to impact luminaire reliability than LEDs.

As the number of available large and many-faceted computer models continues to increase, simulating complex systems by coupling existing models of smaller subsystems becomes more attractive because of advantages such as leveraging existing programming. Advances in computational technologies also contribute to the increased feasibility of coupled systems. Although coupled systems may be used to study new problems that their constituent models could not address, the coupling process brings its own challenges. The modeler may face the task of coupling models from a heterogeneous environment of development platforms, programming languages, and model assumptions. Moreover, the modeler may wish to allow constituent models to be replaced or upgraded without significant difficulty. We discuss a model coupling approach that attempts to address these issues. In our approach, the models run as separate executable processes and store data in a database for later retrieval by other models. While the approach does not prescribe any particular database design, we do suggest elements that are likely to appear. We describe a proof-of-concept application of the approach and evaluate how well our approach meets its goals.

Although solid-state lighting (SSL) products are often intended to have product lifetimes of 15 years or more, the rapid change in technology has created a need for accelerated life tests (ALTs) that can be performed in the span of several months. A critical element of interpreting results from any systems-level ALT is understanding of the impact of the test environment on each component. Because of its ubiquity in electronics, the use of temperature-humidity environments as potential ALTs for SSL luminaires was investigated. Results from testing of populations of three commercial 6” downlights in environments of 85°C and 85% relative humidity (RH) and 75°C and 75% RH are reported. These test environments were found to accelerate lumen depreciation of the entire luminaire optical system, including LEDs, lenses, and reflectors. The effects of aging were found to depend strongly on both the optical materials that were used and the design of the luminaire; this shows that the lumen maintenance behavior of SSL luminaires must be addressed at the optical systems level. Temperature-Humidity ALTs can be a useful test in understand lumainaire depreciation provided that proper consideration is given to the different aging rates of various materials. Since the impact of the temperature-humidity environment varies among components of the optical system, uniform aging of all system components in a single test is difficult to achieve.

Next to energy efficiency, long life is probably the most publicized of solidstate lighting’s (SSL) potential advantages, and plays a key role in any cost-benefit analysis. To accommodate the rapid evolution of SSL technologies and fully realize their energy-savings potential, there is a widespread need in the lighting industry to understand potential failure modes of luminaires. LED luminaires are composed of many working parts, each of which could impact product reliability, so a systems approach is needed to understand failure rates, and merely relying on LED lumen maintenance as a proxy for luminaire lifetime is inaccurate. Long LED lifetimes may not be realized at the luminaire level if, for example, the drivers fail prematurely or the lenses become cloudy. Clearly, developing a library of potential failure modes for LED luminaires, and not just the LEDs, is necessary to estimate the lifetime of these devices.

Municipal Solid Waste Management (MSWM) is a very complex problem present in many communities around the world. Decision makers need to formulate solutions that consider multiple goals and strategies. Strategies include multiple options for waste collection, transportation, transfer, treatment and disposal. The most appropriate choice, however, is often not clear. Given the large number of available options for MSWM and the interrelationships among these options, identifying MSWM strategies that satisfy economic or environmental objectives is a complex task. The main objective of this work is to use MSWM simulation and multi-objective linear programming to support decision makers in the process of selecting MSWM strategies from a very large decision space and in the presence of multiple objectives. Three competing objectives are considered: least cost, minimization of carbon dioxide emissions and minimization of energy consumption. A multi-objective fuzzy linear programming method is proposed to manage imprecision and uncertainty in the objectives via fuzzy membership functions. Keywords-simulation model; linear programming; fuzzy multiobjective optimization; Pareto optimal set; waste management.

Reciclaje en Costa Rica: Balance y perspectivas. Este artículo explora las realidades del reciclaje en Costa Rica, así como su evolución es los últimos años. Se concentra en evaluar los flujos de materiales y los aspectos económicos de dos productos: papel y vidrio. Brevemente evalúa los mismos aspectos para el plástico y el acero. Muestra las siguientes tazas de recuperación: Para papel el 22,22% y para el vidrio 15.5%. Hay tres factores que dificultan el mejoramiento de estas tasas de recuperación: a) ingresos per-cápita crecientes. b) poca educación ambiental en las clases alta y media y c) políticas de compañías grandes y pequeñas, que consisten en la promoción de materiales de envasado, no reutilizables, y en algunos casos difíciles de reciclar. El reciclaje muestra una estructura económica compleja: recolectores informales de la calle, pocos internediarios con grandes márgenes de utilidad y una compañía por cada tipo de producto recicleble, la cual tiene el monopolio de la compra. Los mercado para productos reciclables no trabajan adecuadamente. Costa Rica tiene tres desafíos simultáneos: incrementar las tareas de recuperación, desarrollar mercados para productos reciclables y mejorar el nivel de vida de los recolectores callejeros. Para enfrentar estos retos, se requiere la ayuda del Estado y de las Organizaciones no Gubernamentales

—This paper describes the use of validation methods in model building. We address issues associated with the increasing complexity of models that is in part a response to the growing popularity of Agent-Based Models (ABM), commonly used to study cognitive, natural, and social phenomena. The first section of this manuscript discusses model categories and attributes. The second section discusses the stages of validating a simulation model: verification, validity, and sensitivity analysis. The third section presents specific validation approaches, with an emphasis on six specific tests that are described in detail. The final section summarizes the goals of model validation and modeling.

Increasingly, researchers are turning to computational models to understand the interplay of important variables on systems' behaviors. Although researchers may develop models that meet the needs of their investigation, application limitations-such as nonintuitive user interface features and data input specifications-may limit the sharing of these tools with other research groups. By removing these barriers, other research groups that perform related work can leverage these work products to expedite their own investigations. The use of software engineering practices can enable managed application production and shared research artifacts among multiple research groups by promoting consistent models, reducing redundant effort, encouraging rigorous peer review, and facilitating research collaborations that are supported by a common toolset. This report discusses three established software engineering practices- the iterative software development process, object-oriented methodology, and Unified Modeling Language-and the applicability of these practices to computational model development. Our efforts to modify the MIDAS TranStat application to make it more user-friendly are presented as an example of how computational models that are based on research and developed using software engineering practices can benefit a broader audience of researchers.

This paper describes an integrated solid waste management (ISWM) model to assist in identifying alternative SWM strategies that meet cost, energy, and environmental emissions objectives. An SWM system consisting of over 40 unit processes for collection, transfer, separation, treatment (e.g., combustion, composting), and disposal of waste as well as remanufacturing facilities for processing recycled material is defined. Waste is categorized into 48 items and their generation rates are defined for three types of sectors: single-family dwelling, multifamily dwelling, and commercial. The mass flow of each item through all possible combinations of unit processes is represented in a linear programming model using a unique modeling approach. Cost, energy consumption, and environmental emissions associated with waste processing at each unit process are computed in a set of specially implemented unit process models. A life-cycle approach is used to compute energy consumption and emissions of CO, fossil- and biomass-derived CO2,NOx,SOx, particulate matter, PM10 and greenhouse gases. The model is flexible to allow representation of site-specific issues, including waste diversion targets, mass flow restrictions and requirements, and targets for the values of cost, energy, and each emission. A companion paper describes the application of this model to examine several SWM scenarios for a hypothetical, but realistic, case study.

A companion paper described the development of the integrated solid waste management (ISWM) model that considers cost, energy, and environmental releases associated with management of municipal solid waste. This paper demonstrates the application of the ISWM model to a hypothetical, but realistic, case study. Several solid waste management (SWM) scenarios are studied, including the variation in energy and environmental emissions among alternate SWM strategies; the effect of mandated waste diversion (through recycling and other beneficial uses of waste such as combustion to recover energy) on environmental releases and cost; the tradeoff between cost and the level of waste diversion; and the tradeoff between cost and greenhouse gas emissions. In addition, the flexibility of the model is illustrated by the identification of alternate SWM strategies that meet approximately the same objectives using distinctly different combinations of unit processes. This flexibility may be of importance to local solid waste management planners who must implement new SWM programs. Use of the model illustrates the potential impact of solid waste management policies and regulations on global environmental emissions.

Existing solid waste management (SWM) planning software provides only limited assistance to decision makers struggling to find strategies that address their multifarious concerns. The combinatorial nature (many waste items and many management options) and multiple objectives of the SWM problem severely constrain the effectiveness of a manual search process using these tools. Recognizing this, researchers have proposed several optimization-based search procedures. These methods, however, enjoy limited use due to the substantial expertise required for their application. This paper presents a new computer-based decision support framework that addresses these limitations. The new framework integrates process models that quantify the life-cycle inventory of a range of pollutants and costs for an extensive municipal solid waste system, an optimization search procedure that identifies strategies that meet cost and environmental objectives and site-specific restrictions, and a user-friendly interface that facilitates utilization of these components by practitioners. After describing the software design, the use and value of the tool in typical waste management scenarios is demonstrated through a hypothetical, but realistic, case study in which several alternative SWM strategies are generated and examined.