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At least 559 records · Page 31

A guideline to document occupant behavior models for advanced building controls

The availability of computational power, and a wealth of data from sensors have boosted the development of model-based predictive control for smart and effective control of advanced buildings in the last decade. More recently occupant-behavior models have been developed for including people in the building control loops. However, while important objectives of scientific research are reproducibility and replicability of results, not all information is available from published documents. Therefore, the aim of this paper is to propose a guideline for a thorough and standardized occupant-behavior model documentation. For that purpose, the literature screening for the existing occupant behavior models in building control was conducted, and the occupant behavior modeling processes were studied to extract practices and gaps for each of the following phases: problem statement, data collection, and preprocessing, model development, model evaluation, and model implementation. Here, the literature screening pointed out that the current state-of-the-art on model documentation shows little unification, which poses a particular burden for the model application and replication in field studies. In addition to the standardized model documentation, this work presented a model-evaluation schema that enabled benchmarking of different models in field settings as well as the recommendations on how OB models are integrated with the building system.

Building control↗

Revealing the interplay between “intelligent behavior” and surface reconstruction of non-precious metal doped SrTiO 3 catalysts during methane combustion

The impact of surface reconstruction of a model perovskite, SrTiO 3 (STO), on CH 4 activation for combustion and oxidative coupling was previously revealed that the reaction rate was proportional to the creation of Srterminated step sites. Doped perovskites (SrTi 1-x M x O 3 , M=metal dopant) present yet another form of reconstruction throughout the surface and the bulk, where the metal dopant can migrate in and out of the perovskite lattice, also known as "intelligent behavior". In this work, understanding the interplay between perovskite surface reconstruction (surface termination) and the "intelligent behavior" is tackled for the first time, and the catalytic consequences are probed with CH 4 combustion as a model reaction. A set of experimental techniques, including XRD, Raman spectroscopy, X-ray adsorption spectroscopy, kinetic measurements, as well as DFT calculations were used to understand the catalytic behavior of the reconstructed surfaces of Ni and Cu-doped STO for methane combustion. Here, we found that during methane oxidation, the diffusion of Ni and Cu into the lattice due to the "intelligent behavior" is accompanied by Sr enrichment on the surface of the perovskite. This Srenrichment process is reversible when Cu or Ni species exsolute as clusters/nanoparticles upon H 2 treatment. Such a surface reconstruction is found to greatly impact the catalytic activity of doped perovskites towards methane combustion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Shape memory behavior and recovery force of 4D printed textile functional composites

Four-dimensional (4D) printing of multi-directionally reinforced preforms has tremendous potential for the development of next generation functional composites by using the capabilities of 3D printing technology, 3D textile preform design, and polymer shape memory behavior. This paper demonstrates the shape memory behavior and recovery force of 4D printed circular braided tube preforms and their silicone elastomer matrix composites. The preforms were printed by fused deposition modeling using the shape memory polymer (SMP), polylactic acid (PLA). The effects of braiding angle, tube wall thickness, and shape recovery temperature on the shape memory behavior of 4D printed tube preforms and their silicone elastomer matrix composites have been characterized. Measurements of shape recovery forces of the preform and composite were conducted using dynamic mechanical analysis (DMA). The braided microstructural parameters and shape recovery temperature have a significant effect on the preform shape memory behavior. The introduction of the silicone elastomer matrix greatly enhances the shape recovery force, shape recovery ratio, as well as radial compressive failure load of the 4D printed preform/silicone elastomer matrix composite. Finally, building on these results, a potential application for 4D printed textile functional composites is presented.

42 ENGINEERING↗

Think before you throw! An analysis of behavioral interventions targeting PET bottle recycling in the United States

The United States generates 42 Mt of plastic waste each year and is one of the biggest contributors to ocean plastic waste. Consequently, plastic has become synonymous with the linear economy, and many scholars are studying and proposing circular economy solutions to mitigate plastic pollution. Recycling has received much attention from both social sciences and engineering as a circular economy strategy, but no study has yet quantified how behavioral interventions could asymmetrically affect different populations. Here, this study combines agent-based modeling, material flow analysis, system dynamics, and life cycle assessment to assess the effect of four behavioral interventions on the collection rates of polyethylene terephthalate bottle waste, displaced virgin plastic manufacturing, and avoided greenhouse gas (GHG) emissions. Results show that, while behavioral interventions would require about 300–900 GJ of additional energy at end-of-life due to improved collection rates, they would avoid about 500–700 thousand metric tons of GHG emissions. Results also illustrate the importance of habits in disposal behaviors and show that different forms of interventions can be better adapted to particular social contexts than others. While the circular economy and its application to plastic waste should certainly not be restricted to recycling, this study demonstrates that improved collection rates and recycling technologies can contribute to reducing the amount of plastic waste polluting our oceans.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Explosion behavior investigation and safety assessment of large-format lithium-ion pouch cells

We report large-format lithium-ion (Li-ion) batteries with high energy density for electric vehicles are prone to thermal runaway (or even explosion) under abusive conditions. In this study, overcharge induced explosion behaviors of large-format Li-ion pouch cells with Li[Ni 0.8 Co 0.1 Mn 0.1 ]O 2 cathode at different current rates (C-rates) (0.5C, 1C, 2C) were investigated. The explosion characteristics of the cells were elucidated by discussing the evolution of the cell voltage, the surface temperature and the shock wave pressure. Generally, the whole overcharge process could be divided into four stages according to the evolution of several key parameters and the overcharge behaviors; the overcharge C-rate has a great influence on cells’ thermal behaviors. The experimental results showed that the thermal runaway process of Li-ion cells caused by overcharging consisted of two kinds of explosions, physical explosion and chemical explosion. The existence of observable negative pressure zone in the pressure curves indicated that the Li-ion cells are not a self-supplying oxygen system during the explosion. Further, the explosion dynamics parameters were matched. An explosion TNT-equivalent conversion strategy that depended on the pressure of the shock wave was utilized to evaluate the released energy and its hazards. In addition, with respect to the overcharge of Li-ion pouch cells, a safety assessment method and a safety management method were proposed based on the explosion behaviors. From the perspective of battery safety, this study is of great significance for the safety design of Li-ion cells and can provide guidance for engineers to optimize the safety function of battery packs.

25 ENERGY STORAGE↗

Multiscale modeling of fission gas behavior in U 3 Si 2 under LWR conditions

In this work, we present a model of fission gas behavior in U 3 Si 2 under light water reactor (LWR) conditions for application in engineering fuel performance codes. The model includes components for intra-granular and inter-granular behavior of fission gases. The intra-granular component is based on cluster dynamics and computes the evolution of intra-granular fission gas bubbles and swelling coupled to gas diffusion to grain boundaries. The inter-granular component describes the evolution of grain-boundary fission gas bubbles coupled to fission gas release. Given the lack of experimental data for U 3 Si 2 under LWR conditions, the model is informed with parameters calculated via atomistic simulations. In particular, we derive fission gas diffusivities through density functional theory calculations, and the re-solution rate of fission gas atoms from intra-granular bubbles through binary collision approximation calculations. Further, the developed model is applied to the simulation of an experiment for U 3 Si 2 irradiated under LWR conditions available from the literature. Results point out a credible representation of fission gas swelling and release in U 3 Si 2 . Finally, we perform a sensitivity analysis for the various model parameters. Based on the sensitivity analysis, indications are derived that can help in addressing future research on the characterization of the physical parameters relative to fission gas behavior in U 3 Si 2 . The developed model is intended to provide a suitable infrastructure for the engineering scale calculation of fission gas behavior in U 3 Si 2 that exploits a multiscale approach to fill the experimental data gap and can be progressively improved as new lower-length scale calculations and validation data become available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Observation and Modeling of Dynamic Fracture Behaviors of Battery Cell Under Impact Loading Using Enhanced Representative Volume Element Concept

The burgeoning electric automobile industry has increased interest in battery safety. Battery cells experience significant mechanical stress during operation, including the impact of accidents and vibrations from driving. The potential for thermal runaway reactions in battery cells raises safety concerns. Although numerous researchers have defined the dynamic behavior of battery cells and proposed numerical models to describe it, few studies have focused on the high-strain rate mechanical impact phase correlated with the onset of fracture. In this study, we describe the dynamic behavior of pouch battery cells and propose a modeling method to study their mechanical failure under impact situations. Impact tests are conducted at various velocities and heights. To overcome numerical issues commonly encountered under rapid deformation scenarios, a new finite element model is developed based on the representative volume element model. The proposed approach efficiently simulates continuous crack propagation and brittleness behavior during impact by permitting the individual behavior of the cell components. Therefore, engineers can reliably design safer electric vehicle battery cells by measuring the properties of the cell components.

ENERGY STORAGE↗

Rheological behavior and fiber spinning of polyacrylonitrile (PAN)/Carbon nanotube (CNT) dispersions at high CNT loading

Rheological studies play an important role in polymer processing including fiber spinning. In the current work, rheological behavior has been studied for polyacrylonitrile (PAN)/carbon nanotube (CNT) dispersions in dimethyl formamide (DMF), where CNT loading is as high as 15 wt% of the total solids (polymer + CNT). The presence of CNTs increased the elastic-like and shear thinning behavior of the dispersions. The terminal slope of the log G' versus log G" curve, which was used to characterize the homogeneity of solution or dispersion, is dependent on the CNT concentration but independent of temperature between 0 and 60 °C. PAN/CNT-10 (90 wt% PAN +10 wt% CNT) and PAN/CNT-15 were gel spun at different conditions, with small diameter capillary at high shear rate and large diameter capillary at relatively low shear rate. Additionally, for PAN/CNT-10, fiber spinning with lower molecular weight polymer showed increased continuous jetting time when compared to spinning with higher molecular weight polymer. In addition, the rheological behavior of PAN/cellulose nanocrystal (CNC) dispersion with 20–60 wt% CNC was also compared to that of the PAN/CNT dispersions. PAN/CNC and PAN/CNT share similarities in both rheological behavior and fiber spinning at high filler loading.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessment of occupant-behavior-based indoor air quality and its impacts on human exposure risk: A case study based on the wildfires in Northern California

he recent wildfires in California, U.S., have caused not only significant losses to human life and property, but also serious environmental and health issues. Ambient air pollution from combustion during the fires could increase indoor exposure risks to toxic gases and particles, further exacerbating respiratory conditions. This work aims at addressing existing knowledge gaps in understanding how indoor air quality is affected by outdoor air pollutants during wildfires -- by taking into account occupant behaviors (e.g., movement, operation of windows and air-conditioning) which strongly influence building performance and occupant comfort. A novel modeling framework was developed to simulate the indoor exposure risks considering the impact of occupant behaviors by integrating building energy and occupant behaviour modeling with computational fluid dynamics simulation. Occupant behaviors were found to exert significant impacts on indoor air flow patterns and pollutant concentrations, based on which, certain behaviors are recommended during wildfires. Further, the actual respiratory injury level under such outdoor conditions was predicted. The modeling framework and the findings enable a deeper understanding of the actual health impacts of wildfires, as well as informing strategies for mitigating occupant health risk during wildfires.

54 ENVIRONMENTAL SCIENCES↗

“Teens are from Mars, Adults are from Venus”: Analyzing and Predicting Age Groups with Behavioral Characteristics in Instagram

We present behavioral characteristics of teens and adults in Instagram and prediction of them from their behaviors. Based on two independently created datasets from user profiles and tags, we identify teens and adults, and carry out comparative analyses on their online behaviors. Our study reveals: (1) significant behavioral differences between two age groups; (2) the empirical evidence of classifying teens and adults with up to 82% accuracy, using traditional predictive models, while two baseline methods achieve 68% at best; and (3) the robustness of our models by achieving 76%—81% when tested against an independent dataset obtained without using user profiles or tags.

behavioral patterns and detection of teens in soci↗

A Comparison of Geospatially Modeled Fire Behavior and Potential Application to Fire and Fuels Management for the Savannah River Site

This study evaluates modeled fire behavior for the Savannah River Site in the Atlantic Coastal Plain of the southeastern U.S. using three data sources: FCCS, LANDFIRE, and SWRA. The Fuel Characteristic Classification System (FCCS) was used to build fuelbeds from intensive field sampling of 629 plots. Custom fire behavior fuel models were derived from these fuelbeds. LANDFIRE developed surface fire behavior fuel models and canopy attributes for the U.S. using satellite imagery informed by field data. The Southern Wildfire Risk Assessment (SWRA) developed surface fire behavior fuel models and canopy cover for the southeastern U.S. using satellite imagery.

60 APPLIED LIFE SCIENCES↗

Interactions of aquatic animals with the ORPC OCGen® in Cobscook Bay, Maine: Monitoring behavior change and assessing the probability of encounter with a deployed MHK device

Commercial viability of the marine hydrokinetic (MHK) energy industry is contingent on numerous and diverse factors. A major factor is the effects deployed devices have on animals. This factor is multi-faceted since it is dependent on the availability of appropriate scientific approaches to detect these effects. One of the animal groups with overlapping distributions of MHK devices are fishes. As such, individual fish behavior is likely to be influenced by the presence and operation of MHK devices. Depending on the scale of deployment there are implications for changes to essential fish habitat and effects that can be explored during deployment of a single device yet most changes are likely to be realized when multiple devices are deployed over large areas. It is not only important to document these effects and examine the need for mitigation, but also determine whether the methods involved can be used within the economic constraints of this nascent industry. The results presented in this report benefit the MHK industry by providing transferrable environmental monitoring approaches for MHK projects, specifically related to the interactions between static and dynamic tidal turbines and fish. In addition, some of the data can be used to generalize conditions (e.g., the temporal periodicity of fish presence in tidal regions and probability of fish encountering a device) at other MHK sites with similar physical conditions and fish assemblages. Ocean Renewable Power Company, LLC (ORPC) deployed and tested a prototype OCGen® tidal module in Cobscook Bay, Maine, in the summer of 2014. University of Maine researchers proposed an approach to inform other researchers, regulators, and industry members of the effects of this deployment on fish. While the approach was specifically applied to the OCGen® module, results are applicable to other pilot projects and inform future array deployments. Research funded under this grant allowed us to quantify fish presence as well as individual and group-level behavior changes in the presence of the deployed OCGen® module along with a bottom support frame from a previously deployed device (TidGen®). Specific objectives associated with fish behavior changes were (1) continuation of two long-term datasets: (a) stationary down-looking hydroacoustic dataset near an MHK device (group-level) and (b) stationary side-looking hydroacoustics near the bottom-support frame of a previously deployed MHK device (individual-level); (2) application of new processing methods to down-looking hydroacoustic datasets to improve fish species identification (group-level); and (3) development of an encounter probability model using data on fish abundance, vertical distribution, and behavior.

16 TIDAL AND WAVE POWER↗

Conflicting Information and Compliance With COVID-19 Behavioral Recommendations

The prevalence of COVID-19 is shaped by behavioral responses to recommendations and warnings. Available information on the disease determines the population’s perception of danger and thus its behavior; this information changes dynamically, and different sources may report conflicting information. We study the feedback between disease, information, and stay-at-home behavior using a hybrid agent-based-system dynamics model that incorporates evolving trust in sources of information. We use this model to investigate how divergent reporting and conflicting information can alter the trajectory of a public health crisis. The model shows that divergent reporting not only alters disease prevalence over time, but also increases polarization of the population’s behaviors and trust in different sources of information.

59 BASIC BIOLOGICAL SCIENCES↗

Computing Legacy Software Behavior to Understand Functionality and Security Properties: An IBM/370 Demonstration

Organizations maintaining mainframe legacy software can benefit from code modernization and incorporation of security capabilities to address the current threat environment. Oak Ridge National Laboratory is developing the Hyperion system to compute the behavior of software as a means to gain understanding of software functionality and security properties. Computation of functionality is critical to revealing security attributes, which are in fact specialized functional behaviors of software. Oak Ridge is collaborating with MITRE Corporation to conduct a demonstration project to compute behavior of legacy IBM Assembly Language code for a federal agency. The ultimate goal is to understand functionality and security vulnerabilities as a basis for code modernization. This paper reports on the first phase, to define functional semantics for IBM Assembly instructions and conduct behavior computation experiments.

reverse engineering↗

Behavior-Based Budget Management Using Predictive Analytics

Historically, the mechanisms to perform forecasting have primarily used two common factors as a basis for future predictions: time and money. While time and money are very important aspects of determining future budgetary spend patterns, organizations represent a complex system of unique individuals with a myriad of associated behaviors and all of these behaviors have bearing on how budget is utilized. When looking to forecasted budgets, it becomes a guessing game about how budget managers will behave under a given set of conditions. This becomes relatively messy when human nature is introduced, as different managers will react very differently under similar circumstances. While one manager becomes ultra conservative during periods of financial austerity, another might be un-phased and continue to spend as they have in the past. Both might revert into a state of budgetary protectionism masking what is truly happening at a budget holder level, in order to keep as much budget and influence as possible while at the same time sacrificing the greater good of the organization. To more accurately predict future outcomes, the models should consider both time and money and other behavioral patterns that have been observed across the organization. The field of predictive analytics is poised to provide the tools and methodologies needed for organizations to do just this: capture and leverage behaviors of the past to predict the future.

99 GENERAL AND MISCELLANEOUS↗

The Role of Awards Programs in Stimulating Energy Efficient Behavior: A Study of Award Winners

The value of formal awards programs may be principally in gaining wider recognition for achievements in energy efficiency. But how do these programs contribute to the goal that is presumably behind this value, i.e., stimulating further energy efficient behavior, beyond publicizing the awards ceremonies and describing the projects via websites, posters, and the like? Interviews with 22 individuals and teams of award winners under the Department of Energy Federal Energy Management Program (DOE FEMP) yield insights on the roles that awards programs can play in stimulating energy efficient behavior, especially with regard to institutional dimensions of such behavior. Award winners identified institutional facilitators and barriers in their projects and programs as well as factors in their implementation processes, thus providing information that can guide other efforts. Although only one of the interviewees affirmed that winning an award was a motivating factor, awards do validate often-hard-won achievements through recognition and, in some cases, additional resources, thus stimulating both the winners themselves and those who see the achievements to further energy-saving activities. Finally, award winners’ responses demonstrated the importance of behavioral and institutional change in energy efficiency.

awards programs↗

Elemental Solubility Tendency for the Phases of Uranium by Classical Models Used to Predict Alloy Behavior

Traditional alloy theory models, specifically Darken-Gurry and Miedema’s analyses, that characterize solutes in solid solvents relative to physical properties of the elements have been used to assist in predicting alloy behavior. These models will be applied relative to the three solid phases of uranium: alpha (orthorhombic), beta (tetragonal), and gamma (bcc). These phases have different solubilities for specific alloy additions as a function of temperature. The Darken-Gurry and Miedema models, with modifications based on concepts of Waber, Gschneider, and Brewer will be used to predict the behavior of four types of solutes: 1) Transition metals that are used for various purposes associated with the containment as alloy additions in the uranium fuel 2) Transuranic elements in the uranium 3) Rare earth fission products (lanthanides) 4) Transition metals and other fission products Using these solute map criteria, elemental behavior will be predicted as highly soluble, marginally soluble, or immiscible (compound formers) and will be used to compare solute effects during uranium phase transformations. The overlapping of these solute maps are convenient first approximation tools for predicting alloy behavior.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Behavioral and neuroinflammatory changes caused by glyphosate: Base herbicide in mice offspring

Abstract Background Glyphosate is a pesticide considered of low toxicity, but scientific evidences show it can be harmful to health. This study aimed to evaluate the toxicity in mice offspring exposed to glyphosate‐based herbicide (GBH) during the intrauterine period. Methods Female matrices received glyphosate 0.3 mg/kg daily per oral throughout the gestational period, which was variable between 18 and 22 days. From the 25th until the 28th days post‐birth, mice offspring were subjected to behavioral tests, and the prefrontal cortex was processed for immunohistochemical analysis. Results Two significant behavioral changes were observed: anxiety in the GLIF0.3 group, increase in the behavior burying marbles in the marble‐burying test and hyperactivity, expressed by the significant increase of the crossing number in the open field test. The increased microglia, TNF‐alpha, and astrocyte expression were also observed in the prefrontal cortex of offspring treated with GLIF0.3. Conclusion Exposure to GBH during mice intrauterine development induces hyperactive and anxious behavior, evidencing neuroinflammation.

de Castro Vieira Carneiro, Carla Larissa↗