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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Cyberattack Detection for Cyber Physical Systems Security–A Preliminary Study.

Cyber-physical systems (CPS) security has become an increasingly important research topic in recent years. Geared towards more advanced cyberattack detection techniques as part of strategies for enhancing the security of CPS, in this paper we propose a machine learning based cyber-attack detection scheme. The proposed scheme is a physical-domain technique; specifically, it assumes the physical measurements of the system carry sufficient information for capturing the system behavior, thus can be used for differentiating normal operation and attacks. CPS are complex in nature and the number of physical measurements available for CPS is often overwhelmingly high. Thus, accurately modeling CPS’ dynamic behavior, more importantly, distinguishing normal and adversary activities based on the large number of physical measurements, can be challenging. To address the challenge, we have focused our research effort on feature engineering, that is, to intelligently derive a set of salient signatures or features from the noisy measurements. We make sure the derived features are more compact and, more importantly, have more discriminant power than the original physical measurements, thus enabling us to achieve more accurate and robust detection performance. To demonstrate the effectiveness of the proposed scheme, in our experimental study we consider gas turbines of combined cycle power plants as the cyberphysical system. Using the data from the high-fidelity simulation we show that our proposed cyberattack detection scheme is able to achieve high detection performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Development of one-dimensional computational fluid dynamics code 'GFLOW' for groundwater flow and contaminant transport analysis

Prediction of groundwater movement and contaminant transport in soil is an important problem in many branches of science and engineering. This includes groundwater hydrology, environmental engineering, soil science, agricultural engineering and also nuclear engineering. Specifically, in nuclear engineering it is applicable in the design of spent fuel storage pools and waste management sites in the nuclear power plants. Ground water modeling involves the simulation of flow and contaminant transport by groundwater flow. In the context of contaminated soil and groundwater system, numerical simulations are typically used to demonstrate compliance with regulatory standard. A one-dimensional Computational Fluid Dynamics code GFLOW had been developed based on the Finite Difference Method for simulating groundwater flow and contaminant transport through saturated and unsaturated soil. The code is validated with the analytical model and the benchmarking cases available in the literature. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Development of Membrane Distillation Technology Utilizing Waste Heat for Treatment of High Salinity Wastewaters

Membrane distillation (MD) can serve as a cost effective method to treat high salinity wastewaters, especially if waste heat is utilized for its operation. The goal of this work is to study the feasibility of employing MD technology for the treatment of high salinity wastewaters which are generated as a result of natural gas production and active reservoir management for CO 2 sequestration. This study also aimed at quantifying the availability of waste heat which could be used as the primary source of thermal energy to drive the MD process. Bench scale studies were carried out with several commercially available membranes using both synthetic and actual high salinity wastewaters. The membranes tested with real wastewater samples exhibited excellent rejection of dissolved ions, including naturally occurring radioactive material (NORM). Long term bench scale experiments with real produced water from the Marcellus shale play revealed that iron oxide could precipitate on the feed side of direct contact MD (DCMD) module but had a negligible effect on the performance of the system. Based on the bench scale experiments, an ASPEN Plus simulation, which incorporated a mathematical model with fundamental heat and mass transfer equations, was developed and used to evaluate the process energy requirements. Despite low operating temperature and pressure for MD, it had a large thermal energy requirement for operation, which could make this technology expensive compared to reverse osmosis (RO) and forward osmosis (FO). However, it is important to note that RO and FO have limited applicability for high salinity shale gas wastewater. Moreover, MD could be integrated with renewable energy sources such as wind or solar energy or industrial waste heat sources to offset the thermal energy requirements and enhance the economics of wastewater treatment. Natural gas compressor stations (NG CS) have been proposed in this study as the source of waste heat based on the estimate of quantity and quality of available waste heat in the exhaust streams of gas turbine and internal combustion compressor engines. Using the actual installed capacity and location of compressor stations in the U.S., this analysis revealed that an average of 610 TJ/day of thermal energy is available at existing NG CS and that this source of waste heat is of high quality with temperatures above 645 K. A systems-level integration of MD with waste heat from NG CS revealed that approximately 56% of available waste heat at NG CS in Pennsylvania is sufficient to concentrate (from 10% to 30% salinity) all wastewater associated with shale gas extraction. Techno-economic assessment (TEA) accounting for capital as well as operating and maintenance costs with and without waste heat integration was conducted for a hypothetical 0.5 million gallons per day (MGD) DCMD plant using experimental and modeling results from this study. TEA revealed that the total cost of shale gas wastewater treatment using MD is $5.7/m 3 feed for the base case scenario in which the thermal energy requirements are met by external steam, however, the total cost can be reduced to $0.74/m 3 feed when integrated with free waste heat from NG CS. Sensitivity analysis revealed that thermal energy cost and feed TDS are the most important factors in total cost of high salinity wastewater treatment using DCMD.

03 NATURAL GAS↗
DOE OSTI2018

The Building ENergy Demand (BEND) Model: A Comprehensive Composite Building Energy Modeling Framework

The Building ENergy Demand (BEND) model was developed at Pacific Northwest National Laboratory (PNNL) to simulate climate-dependent hourly building energy demand with the ability to disaggregate down to or aggregate up to any geographic area of interest, including counties, states, electric utility service territories, and census regions. The BEND modeling framework is designed to study the effects of climate change, economics, technology advancement, and various mitigation policies on aggregate building energy demand. To make the process computationally feasible, BEND reduces granularity in building characteristics and weather forcing while maintaining enough detail to minimize systematic differences (biases) between BEND results and data from the Energy Information Administration (EIA). Based on the Commercial Building Energy Consumption Survey (CBECS) and Residential Energy Consumption Survey (RECS) databases, BEND establishes a set of representative buildings with predefined sets of building types, sizes, and vintages. These representative buildings are defined for each of the four U.S. census regions and the five climate zones used by the EIA for building surveys (hereafter “EIA climate zones”). BEND’s representative buildings are based on a statistical analysis of the CBECS and RECS databases that infers detailed parameters such as construction type, thermal properties, internal loads, equipment and mechanical systems, and operation schedules from the high-level descriptors in those databases (building type, vintage, size, and location). The representative buildings are simplified and consolidated into a set of prototype buildings for the purpose of simulating building energy demand. Combining the prototype buildings with weather files from selected locations and years, BEND creates a set of simulation-ready building models to be run using the EnergyPlus simulation engine (EnergyPlus). The base spatial unit of each BEND simulation is a subregion that is the intersection of an International Energy Conservation Code climate zone, a census region, and an EIA climate zone; analysis for each spatial unit is influenced by the weather file BEND selects to represent the climate-similar area. The major simulation outputs of interest to BEND are hourly energy consumption values for each simulated year, possibly for multiple fuel types. Based on building-stock weights derived from the CBECS/RECS data, the hourly output streams are aggregated to a single, 8760-hour load profile for each of the major building categories—residential and commercial—with the possibility of segregating by fuel types. To correct for biases inherent in the use of a limited suite of representative buildings, BEND is calibrated against observational targets of total annual building energy consumption and hourly load profiles (including peak demand) obtained for the decision-relevant geographic scales of interest (e.g., total electric load data for individual balancing authorities available from EIA). Based on available data such as population distribution, BEND is able to aggregate both up and down scales, allowing the study of building energy demand over a range of spatial scales (e.g., states or counties within the Western Electricity Coordinating Council, Eastern Interconnection, or the entire U.S.) and/or subsets of building types (e.g., office buildings with particular size ranges).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Multiphysics simulations of Self-Regulating performance of an optimized molten metal fuel microreactor design

Advanced microreactors are expected to play an indispensable role in reliable energy solutions for civilian/ military applications in off-grid regions and space applications such as power supplies for Lunar and Mars bases. An innovative fast neutron spectrum heat pipe microreactor (HP-MR) concept was recently proposed with two unique features: molten U-Mn fuel and heat pipes as the heat removal mechanism. The microreactor was designed to be self-regulated, solely relying on reactivity feedbacks from fuel temperature. The reactor design has been further optimized to provide sufficient engineering safety margin and effective heat removal. In this study, the self-regulating performance of the optimized molten metal fuel microreactor was investigated by multi-physics simulations (neutronics, heat-transfer and heat pipe modeling) based on the MOOSE MultiApps system. In conclusion, the responses of the reactor to a series of transient scenarios were simulated to demonstrate the exceptional and inherent safety features of the novel microreactor concept.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Multifidelity computing for coupling full and reduced order models

Hybrid physics-machine learning models are increasingly being used in simulations of transport processes. Many complex multiphysics systems relevant to scientific and engineering applications include multiple spatiotemporal scales and comprise a multifidelity problem sharing an interface between various formulations or heterogeneous computational entities. To this end, we present a robust hybrid analysis and modeling approach combining a physics-based full order model (FOM) and a data-driven reduced order model (ROM) to form the building blocks of an integrated approach among mixed fidelity descriptions toward predictive digital twin technologies. At the interface, we introduce a long short-term memory network to bridge these high and low-fidelity models in various forms of interfacial error correction or prolongation. The proposed interface learning approaches are tested as a new way to address ROM-FOM coupling problems solving nonlinear advection-diffusion flow situations with a bifidelity setup that captures the essence of a broad class of transport processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Modeling and Simulation of HVAC Faulty Operations and Performance Degradation due to Maintenance Issues

Almost half of the total energy used in the U.S. buildings is consumed by heating, ventilation and air conditionings (HVAC) according to EIA statistics. Among various driving factors to energy performance of building, operations and maintenance play a significant role. Many researches have been done to look at design efficiencies and operational controls for improving energy performance of buildings, but very few study the impacts of HVAC systems maintenance. Different practices of HVAC system maintenance can result in substantial differences in building energy use. If a piece of HVAC equipment is not well maintained, its performance will degrade. If sensors used for control purpose are not calibrated, not only building energy usage could be dramatically increased, but also mechanical systems may not be able to satisfy indoor thermal comfort. Properly maintained HVAC systems can operate efficiently, improve occupant comfort, and prolong equipment service life. In the paper, maintenance practices for HVAC systems are presented based on literature reviews and discussions with HVAC engineers, building operators, facility managers, and commissioning agents. We categorize the maintenance practices into three levels depending on the maintenance effort and coverage: 1) proactive, performance-monitored maintenance; 2) preventive, scheduled maintenance; and 3) reactive, unplanned or no maintenance. A sampled list of maintenance issues, including cooling tower fouling, boiler/chiller fouling, refrigerant over or under charge, temperature sensor offset, outdoor air damper leakage, outdoor air screen blockage, outdoor air damper stuck at fully open position, and dirty filters are investigated in this study using field survey data and detailed simulation models. The energy impacts of both individual maintenance issue and combined scenarios for an office building with central VAV systems and central plant were evaluated by EnergyPlus simulations using three approaches: 1) direct modeling with EnergyPlus, 2) using the energy management system feature of EnergyPlus, and 3) modifying EnergyPlus source code. The results demonstrated the importance of maintenance for HVAC systems on energy performance of buildings. The research is intended to provide a guideline to help practitioners and building operators to gain the knowledge of maintaining HVAC systems in efficient operations, and prioritize HVAC maintenance work plan. The paper also discusses challenges of modeling building maintenance issues using energy simulation programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

A Novel Data-based Stochastic Distribution Control for Non-Gaussian Stochastic Systems

In this note, we present a novel data-based approach to investigate the non-Gaussian stochastic distribution control problem. As the motivation of this note, the existing methods have been summarised regarding to the drawbacks, for example, neural network weights training for unknown stochastic distribution and so on. To overcome these disadvantages, a new transformation for dynamic probability density function is given by kernel density estimation using interpolation. Based upon this transformation, a representative model has been developed while the stochastic distribution control problem has been transformed into an optimisation problem. Then, data-based direct optimisation and identification-based indirect optimisation have been proposed. In addition, the convergences of the presented algorithms are analysed and the effectiveness of these algorithms has been evaluated by numerical examples. In summary, the contributions of this note are as follows: 1) a new data-based probability density function transformation is given; 2) the optimisation algorithms are given based on the presented model; and 3) a new research framework is demonstrated as the potential extensions to the existing stochastic distribution control.

42 ENGINEERING↗
DOE OSTI2022

Multi-Physics Coupled Seismic Safety Analysis of Molten-Salt Reactors

Pool-type Molten Salt Reactors (MSRs) are a promising advanced nuclear reactor concept relying on passive physical behavior to provide increased safety characteristics. The high heat capacity, high boiling point, unpressurized liquid salt contains the nuclear fuel and as it passes through the vessel achieves criticality and produces nuclear power. The salt then carries away the heat produced along with the delayed neutron precursors towards heat exchangers and primary pumps before entering the core. This forms a highly coupled multiphysics problem between neutronics and fluid flow, which makes modeling these reactors challenging. The safety/licensing case heavily relies on modeling and simulation to prove their safety, and significant effort has been expanded by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to develop the appropriate simulation tools. Their safety/licensing will require a thorough analysis of their behavior during earthquake-based transients. Earthquakes are a transient condition commonly experienced in many regions, and are safely survived by dozens of reactors every year. Nonetheless, significant conservatisms were introduced with limited predictive modeling and simulation available. The first-of-a-kind capability developed by this research will allow for engineers to analyze ranges of design-basis and beyond-design basis accident scenarios to assess the integrity of the reactor vessel and surrounding system, possibly allowing for limiting the costly conservatisms in the design. This projects uses MASTODON, Griffin, and Pronghorn in the NEAMS ecosystem to model the coupled multiphysics problem posed by an earthquake in a molten salt reactor. It marches through a number of number of coupling schemes, from uncoupled simulations to tightly two-way coupled simulations. The appropriate level of coupling for these simulations will then be determined based on the accuracy in the quantities of interest (QoI) and computational effort involved in each scheme. The QoIs chosen for this paper include the mass flow rate across the heat exchanger (for Pronghorn simulations), power output of the reactor (for Griffin simulations), and the maximum Von Mises stress (for MASTODON simulations). This summary paper reports on the current progress of this project, with 2D tightly coupled multiphysics results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Comprehensive uncertainty quantification (UQ) for full engineering models by solving probability density function (PDF) equation

This report details a new method for propagating parameter uncertainty (forward uncertainty quantification) in partial differential equations (PDE) based computational mechanics applications. The method provides full-field quantities of interest by solving for the joint probability density function (PDF) equations which are implied by the PDEs with uncertain parameters. Full-field uncertainty quantification enables the design of complex systems where quantities of interest, such as failure points, are not known apriori. The method, motivated by the well-known probability density function (PDF) propagation method of turbulence modeling, uses an ensemble of solutions to provide the joint PDF of desired quantities at every point in the domain. A small subset of the ensemble is computed exactly, and the remainder of the samples are computed with approximation of the driving (dynamics) term of the PDEs based on those exact solutions. Although the proposed method has commonalities with traditional interpolatory stochastic collocation methods applied directly to quantities of interest, it is distinct and exploits the parameter dependence and smoothness of the dynamics term of the governing PDEs. The efficacy of the method is demonstrated by applying it to two target problems: solid mechanics explicit dynamics with uncertain material model parameters, and reacting hypersonic fluid mechanics with uncertain chemical kinetic rate parameters. A minimally invasive implementation of the method for representative codes SPARC (reacting hypersonics) and NimbleSM (finite- element solid mechanics) and associated software details are described. For solid mechanics demonstration problems the method shows order of magnitudes improvement in accuracy over traditional stochastic collocation. For the reacting hypersonics problem, the method is implemented as a streamline integration and results show very good accuracy for the approximate sample solutions of re-entry flow past the Apollo capsule geometry at Mach 30.

42 ENGINEERING↗
DOE OSTI2025

Conformational Dynamics and Catalytic Backups in a Hyper-thermostable Engineered Archaeal Protein Tyrosine Phosphatase

Protein tyrosine phosphatases (PTPs) are a family of enzymes that play important roles in regulating cellular signaling pathways. The activity of these enzymes is regulated by the motion of a catalytic loop that places a critical conserved aspartic acid side chain into the active site for acid–base catalysis upon loop closure. These enzymes also have a conserved phosphate-binding loop that is typically highly rigid and forms a well-defined anion-binding nest. The intimate links between loop dynamics and chemistry in these enzymes make PTPs an excellent model system for understanding the role of loop dynamics in protein function and evolution. In this context, archaeal PTPs, which have often evolved in extremophilic organisms, are highly understudied, despite their unusual biophysical properties. We present here an engineered chimeric PTP (ShufPTP) generated by shuffling the amino acid sequence of five extant hyperthermophilic archaeal PTPs. Despite ShufPTP’s high sequence similarity to its natural counterparts, it presents a suite of unique properties, including high flexibility of the phosphate binding P-loop, facile oxidation of the active-site cysteine, mechanistic promiscuity, and, most notably, hyperthermostability, with a denaturation temperature likely >130 °C (>8 °C higher than the highest recorded growth temperature of any archaeal strain). Our combined structural, biochemical, biophysical, and computational analysis provides insight both into how small steps in evolutionary space can radically modulate the biophysical properties of an enzyme and showcases the tremendous potential of archaeal enzymes for biotechnology, to generate novel enzymes capable of operating under extreme conditions.

archaea↗
DOE OSTI2019

Natural and Engineered Features Supporting Environmental Performance of Idaho National Laboratory's Remote-Handled Low-Level Waste Disposal Facility - 19436

The Idaho National Laboratory's (INL's) Remote-Handled Low-Level Waste (RH LLW) Disposal Facility has been designed and constructed to receive waste generated at the INL site in support of the US DOE Office of Nuclear Energy (NE) and Naval Reactors (NR) missions. The facility has been designed to receive legacy RH LLW currently in storage at INL facilities and new waste generated by nuclear research programs. RH LLW to be received at the facility is solid waste consisting of surface contaminated materials; ion exchange resins used to purify cooling and canal water; and activated metal components generated during reactor core change outs and Naval spent fuel management; and nuclear R and D. Disposal of INL's RH LLW poses unique disposal challenges due to high radiation levels (contact rates up to 600 Sv/hr [60,000 Rem/hr]) that require remote handling and adequate shielding for transportation and disposal. The facility has been designed to meet the requirements of DOE Order 435.1, Radioactive Waste Management, including the all-pathways dose, air pathway dose, inadvertent intruder doses, and radon emissions limits. This paper presents an overview of natural and engineered design features that support the safety case and enhance the environmental performance of the facility. These features include location selection, use of reinforced pre-cast concrete vaults; a robust hydraulic drainage system; use of steel waste canisters for waste disposal; the facility monitoring system; facility layout; and crediting waste forms. The facility performance assessment (PA) developed to meet the requirements of DOE Order 435.1, credits each of these protective features. Releases from waste forms disposed of at this facility are limited by corrosion of the steel waste canisters which will ultimately allow contact with infiltrating water followed by transport of radionuclides from the vault system. The steel waste canisters were credited for their ability to limit water contact with the waste based on the demonstrated ability of the reinforced pre-caste concrete vaults to provide long-term structural protection of the steel waste canisters. Verification of hydraulic and concrete performance was conducted through laboratory data, field infiltration tests supported by a robust monitoring system, and numerical modeling. Releases into the vault system from activated metals are based on site-specific corrosion data. Radionuclide transport from the vault system from all waste forms is based on site-specific climatological, hydrologic, and stratigraphic data. At INL, the groundwater pathway historically and appropriately has received the most attention. By crediting aspects of the natural system, the engineered vault system, and the waste, estimated radiologic doses via the groundwater pathway are minimal. Air pathway doses were reduced by differentially crediting corrosion of aluminum and stainless steel activated metals resulting in the pathway being screened out of the PA. Groundwater and inadvertent intruder doses were reduced through selective facility layout. This paper provides an overview of the system-wide protective features incorporated into the facility design along with an extensive reference list to supporting technical papers and analyses that provide data and interpretation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Simulation-based assessment of ASHRAE Guideline 36, considering energy performance, indoor air quality, and control stability

This study assesses American Society of Heating, Refrigerating and Air-Conditioning Engineers Guideline 36 (G36) with a typical medium office building. Specifically, this study employed a Modelica model of a variable air volume (VAV) system that serves this building, which includes components for representing indoor virus transmission and filtration. It then implemented the G36 control sequences for both water-side and air-side equipment in Python. After that, this study conducted the assessment by co-simulating G36 and the Modelica model using the Building Operations Testing Framework. Unlike existing works, this work has three unique features: (1) It considers the interactions between control sequences for water-side and air-side equipment of the studied VAV system. (2) It assesses the performance of G36 from the perspective of IAQ. (3) It examines the short-term behaviors of the studied building under G36 to understand the control stability. This assessment confirms significant energy savings from G36, largely because of the interaction between supply air temperature and hot water controls. It also reveals a trade-off between the ability to slow the spread of virus and the energy performance via demand controlled ventilation. Lastly, it emphasizes the necessity of tuning local feedback control when implementing G36.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Dynamic Metabolic Model Building Based on the Ensemble Modeling Approach

Ensemble modeling of kinetic systems addresses the challenges of kinetic model construction, with respect to parameter value selection, and still allows for the rich insights possible from kinetic models. This project aimed to show that constructing, implementing, and analyzing such models is a useful tool for the metabolic engineering toolkit, and that they can result in actionable insights from models. Key concepts are developed and deliverable publications and results are presented.

09 BIOMASS FUELS↗
DOE OSTI2024

Reinforcement learning applied to dilute combustion control for increased fuel efficiency

To reduce the modeling burden for control of spark-ignition engines, reinforcement learning (RL) has been applied to solve the dilute combustion limit problem. Q-learning was used to identify an optimal control policy to adjust the fuel injection quantity in each combustion cycle. A physics-based model was used to determine the relevant states of the system used for training the control policy in a data-efficient manner. The cost function was chosen such that high cycle-to-cycle variability (CCV) at the dilute limit was minimized while maintaining stoichiometric combustion as much as possible. Experimental results demonstrated a reduction of CCV after the training period with slightly lean combustion, contributing to a net increase in fuel conversion efficiency of 1.33%. To ensure stoichiometric combustion for three-way catalyst compatibility, a second feedback loop based on an exhaust oxygen sensor was incorporated into the fuel quantity controller using a slow proportional-integral (PI) controller. The closed-loop experiments showed that both feedback loops can cooperate effectively, maintaining stoichiometric combustion while reducing combustion CCV and increasing fuel conversion efficiency by 1.09%. Finally, a modified cost function was proposed to ensure stoichiometric combustion with a single controller. In addition, the learning period was shortened by half to evaluate the RL algorithm performance on limited training time. Experimental results showed that the modified cost function could achieve the desired CCV targets, however, the learning time was reduced by half and the fuel conversion efficiency increased only by 0.30%.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Multifamily Tool for Energy Audits (MulTEA) Engineering Manual (Version 1)

The Multifamily Tool for Energy Audits (MulTEA) is an energy audit tool designed to provide auditors with an improved energy simulation tool for multifamily buildings and an improved tool for identifying cost-effective energy-efficiency retrofit measures for multifamily buildings. MulTEA is designed specifically to help states and local weatherization agencies implement the Department of Energy (DOE) Weatherization Assistance Program. MulTEA was developed jointly by the Oak Ridge National Laboratory (ORNL) and the Lawrence Berkeley National Laboratory (LBNL). MulTEA is part of ORNL’s web-based Weatherization Assistant suite of audit tools (https://weatherization.ornl.gov/softwaredescription/). The energy calculation engine including the DOE- 2 simulation model and supplementary calculation modules is shared by MulTEA and LBNL’s Home Energy Saver pro (HESpro) (http://hespro.lbl.gov/pro/). On the ORNL side, the energy calculation engine is coupled with a user interface and output reporting capabilities based on Weatherization Assistance Program regulations and guidelines pertinent to MulTEA. On the LBNL side, the same engine will be used in HESpro to expand it to handle multifamily buildings. MulTEA is designed to address small and large multifamily buildings with decentralized and centralized heating, ventilation, and air-conditioning (HVAC) and domestic hot water (DHW) systems. Version 1 of MulTEA addresses small multifamily buildings with decentralized HVAC systems, and decentralized or centralized DHW systems. The capability to model large buildings and centralized HVAC systems will be incorporated in Version 2.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2011

Residential Real-time Price Response Simulation

The electric industry is gaining experience with innovative price responsive demand pilots and limited roll-outs to customers. One of these pilots is investigating real-time pricing signals to engage end-use systems and local distributed generation and storage in a distributed optimization process. Attractive aspects about the approach include strong scalability characteristics, simplified interfaces between automation devices, and the adaptability to integrate a wide variety of devices and systems. Experience in this nascent field is revealing a rich array of for engineering decisions and the application of complexity theory. To test the decisions, computer simulations are used to reveal insights about design, demand elasticity, and the limits of response (including consumer fatigue). Agent-based approaches lend themselves well in the simulation to modeling the participation and interaction of each piece of equipment on a distribution feeder. This paper discusses rate design and simulation experiences at the distribution feeder level where consumers and their HVAC systems and water heaters on a feeder receive real-time pricing signals.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Energize: An Interactive Evaluation Tool for Engaging the General Public with Energy Decision Making - Final Report

The public has an ever-increasing interest in the economic, environmental, and social impacts of global energy production. To support informed decision making, the scientific community has a responsibility to communicate reliable and straight-forward information to the general public, in an engaging way, regarding energy systems and how choices made at different stages of an energy technology life cycle can impact the cost, amount of materials used, and waste produced. Our objective is to enhance public engagement via an interactive electrical energy game (Energ!ze) through which players interact with one another in their quest to develop an electrical energy portfolio that optimizes economic (e.g., company profit), environmental (e.g., reduced CO 2 emissions), and social (e.g., public opinion) impacts. The design and development of Energ!ze was an iterative process involving an interdisciplinary team of engineers, discipline-based scientists, computer scientists, and education experts. The development objectives were two-fold: (1) Accurate and quantifiable modeling of electrical energy systems and (2) Engaging and interactive user interface within the construct of the game narrative. The major game mechanics in the current playable Energ!ze version focus on economic metrics, and the database is scaffolded to add environmental and social metrics for future versions. This report details the outcome of the funding period (Section 2 and 3) and describes the development process, along with recommendations for future development (Section 4).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗