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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
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 OSTI2019

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

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 U.S. Department of Energy (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 debris; ion exchange resins used to purify cooling and canal water; activated metals generated during reactor core change outs and Naval spent fuel management; and nuclear Research & Development. 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 [1], 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 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) [2] developed to meet the requirements of DOE Order 435.1 “Radioactive Waste Management” 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.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

SigTime: Learning and Visually Explaining Time Series Signatures

Understanding and distinguishing temporal patterns in time series data is essential for scientific discovery and decision-making. For example, in biomedical research, uncovering meaningful patterns in physiological signals can improve diagnosis, risk assessment, and patient outcomes. However, existing methods for time series pattern discovery face major challenges, including high computational complexity, limited interpretability, and difficulty in capturing meaningful temporal structures. Here, to address these gaps, we introduce a novel learning framework that jointly trains two Transformer models using complementary time series representations: shapelet-based representations to capture localized temporal structures and traditional feature engineering to encode statistical properties. The learned shapelets serve as interpretable signatures that differentiate time series across classification labels. Additionally, we develop a visual analytics system—SigTime—with coordinated views to facilitate exploration of time series signatures from multiple perspectives, aiding in useful insights generation. We quantitatively evaluate our learning framework on eight publicly available datasets and one proprietary clinical dataset. Additionally, we demonstrate the effectiveness of our system through two usage scenarios along with the domain experts: one involving public ECG data and the other focused on preterm labor analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Highlights of X-Stack ExM Deliverable: MosaStore

This brief report highlights the experience gained with MosaStore, an exploratory part of the X-Stack project “ExM: System support for extreme-scale, many-task applications”. The ExM project proposed to use concurrent workflows supported by the Swift language and runtime as an innovative programming model to exploit parallelism in exascale computers. MosaStore aims to support this endeavor by improving storage support for workflow-based applications, more precisely by exploring the gains that can be obtained from co-designing the storage system and the workflow runtime engine. MosaStore has been developed primarily at the University of British Columbia.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Thermionic emission and energy conversion

This project worked on development of a transformative heat-to-electricity conversion device based on thermionic energy conversion. The research provided a unique opportunity to transform the thermionics technology of the 1950-1990s by applying modern materials and 21st century wafer-scale fabrication methods. Research was conducted to further development of a thermionic energy converter based on modern microfabrication and new low work function anode materials that can surpass all other forms of direct heat-to-electricity conversion. This project completed the following goals: (1) Developed components for use in thermionic energy converters and electron emission devices, including electrode materials for electron emission and electron absorption with ultimate work functions below 5 eV; (2) Designed and fabricated thermionic devices for energy conversion and electron emission based on the components developed in (1); (3) Engineered test systems to characterize electronic, thermal, and mechanical properties of thermionic devices and electron emitters and their components, and test devices and components designed and fabricated in (1) and (2); and (4) Developed theoretical modeling capabilities in support of these technical objectives.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Quantum Analog Coprocessor for Correlated Electron Systems Simulation

Analog quantum simulation is an approach for studying physical systems that might otherwise be computationally intractable to simulate on classical high-performance computing (HPC) systems. The key idea behind analog quantum simulation is the realization of a physical system with a low-energy effective Hamiltonian that is the same as the low-energy effective Hamiltonian of some target system to be studied. Purpose-built nanoelectronic devices are a natural candidate for implementing the analog quantum simulation of strongly correlated materials that are otherwise challenging to study using classical HPC systems. However, realizing devices that are sufficiently large to study the properties of a non-trivial material system (e.g., those described by a Fermi-Hubbard model) will eventually require the fabrication, control, and measurement of at least 0(10) quantum dots, or other engineered quantum impurities. As a step toward large-scale analog or digital quantum simulation platforms based on nanoelectronic devices, we propose a new approach to analog quantum simulation that makes use of the large Hilbert space dimension of the electronic baths that are used to adjust the occupancy of one or a few engineered quantum impurities. This approach to analog quantum simulation allows us to study a wide array of quantum impurity models. We can further augment the computational power of such an approach by combining it with a classical computer to facilitate dynamical mean-field theory (DMFT) calculations. DMFT replaces the solution of a lattice impurity problem with the solution of a family of localized impurity problems with bath couplings that are adjusted to satisfy a self-consistency condition between the two models. In DMFT, the computationally challenging task is the high-accuracy solution of an instance of a quantum impurity model that is determined self-consistently in coordination with a mean-field calculation. We propose using one or a few engineered quantum impurities with adjustable couplings to baths to realize an analog quantum coprocessor that effects the solution of such a model through measurements of a physical quantum impurity, operating in coordination with a classical computer to achieve a self-consistent solution to a DMFT calculation. We focus on implementation details relevant to a number of technologies for which Sandia has design, fabrication, and measurement expertise. The primary technical advances outlined in this report concern the development of a supporting modeling capability. As with all analog quantum simulation platforms, the successful design and operation of individual devices depends critically on one's ability to predict the effective low-energy Hamiltonian governing its dynamics Our project has made this possible and lays the foundation for future experimental implementations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

Simulation of catalytic oxidation and selective catalytic NOx reduction in lean-exhaust hybrid vehicles

We utilize physically-based models for diesel exhaust catalytic oxidation and urea-based selective catalytic NOx reduction to study their impact on drive cycle performance of hypothetical light-duty diesel powered hybrid vehicles. The models have been implemented as highly flexible SIMULINK block modules that can be used to study multiple engine-aftertreatment system configurations. The parameters of the NOx reduction model have been adjusted to reflect the characteristics of Cu-zeolite catalysts, which are of widespread current interest. We demonstrate application of these models using the Powertrain System Analysis Toolkit (PSAT) software for vehicle simulations, along with a previously published methodology that accounts for emissions and temperature transients in the engine exhaust. Our results illustrate the potential impact of DOC and SCR interactions for lean hybrid electric and plug-in hybrid electric vehicles.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Model predictive control of a lean-burn gasoline engine coupled with a passive selective catalytic reduction system

Lean-burn gasoline engines have demonstrated 10–20% engine efficiency gain over stoichiometric engines and are widely considered as a promising technology for meeting the 54.5 miles-per-gallon (mpg) Corporate Average Fuel Economy standard by 2025. Nevertheless, NOx emissions control for lean-burn gasoline for meeting the stringent EPA Tier 3 emission standards has been one of the main challenges towards the commercialization of highly-efficient lean-burn gasoline engines in the United States. Passive selective catalytic reduction (SCR) systems, which consist of a three-way catalyst and SCR, have demonstrated great potentials of effectively reducing NOx emissions for lean gasoline engines but may cause significant fuel penalty due to ammonia generation via rich engine combustion. The purpose of this study is to develop a model-predictive control (MPC) scheme for a lean-burn gasoline engine coupled with a passive SCR system to minimize the fuel penalty associated with passive SCR operation while satisfying stringent NOx and NH3 emissions requirements. Simulation results demonstrate that the MPC-based control can reduce the fuel penalty by 47.7% in a simulated US06 cycle and 32.0% in a simulated UDDS cycle, compared to the baseline control, while achieving over 96% deNOx efficiency and less than 15 ppm tailpipe ammonia slip. The proposed MPC control can potentially enable high engine efficiency gain for highly-efficient lean-burn gasoline engine while meeting the stringent EPA Tier 3 emission standards.

Chen, Pingen↗
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↗