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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Case Study about Energy and Cost Impacts for Different Community Scenarios Using a Community-Scale Building Energy Modeling Tool

The United States building sector consumed approximately 75% of electricity in 2019. By implementing renewable energy technologies and control strategies into buildings, future buildings will serve as energy generators as well as consumers. To accommodate this transition, communications among buildings and between buildings and the grid could provide more possibilities to optimize the energy performance of buildings. This paper develops a community-scale building energy model tool and conducts a case study adopting behind-the-meter distributed energy resources, sharing energy in different buildings, and using different electricity tariff structures. Three scenarios are studied: (1) electricity only supplied by the grid, (2) photovoltaic (PV) panels installed on and available to some but not all buildings, and (3) a connected community. To consider the impacts of locations and energy tariffs, this paper selects four cities and three electricity tariffs to evaluate the energy and cost performances of these three scenarios. The results show that the PV panels in Scenario 2 reduce 25% to 33% of the community-level electricity consumption and 20% to 30% of the community-level electricity cost compared with Scenario 1 in all studied locations and energy tariffs. By considering power management in the connected community (Scenario 3), the electricity consumption and cost can be further reduced by 6% to 7% and 5% to 11%, respectively, compared with Scenario 2.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Development and assessment of a reactor system prognosis model with physics-guided machine learning

Autonomous control systems provide recommendations to help operators in decision-making during plant operations ranging from normal operation to accident management. An important step of autonomous control is prognosis. In nuclear engineering domain, prognosis is the process of predicting future conditions of a system or equipment based on present signs and symptoms of a fault. The prognosis model allows predicting future reactor states for possible candidate control strategies so that the outcomes can be evaluated to determine the best control strategy. The prognosis model requires representing direct relationships between the symptoms and the predictions. In nuclear engineering, computational simulations are approximate representations of the operation of the real system. However, prognosis with computational simulations requires high computation power and time due to possible large number of scenarios. Necessary computation resources can be reduced with machine learning (ML) approach for fast predictions by building a surrogate function using the simulation data. A critical issue is, ML models are ignorant of physical knowledge, and these models approximate statistical relationships between the system variables. This ignorance can produce results that are inconsistent with physical laws, even if an optimal result is achieved from a mathematical point of view. Physics-guided machine learning (PGML) is an approach to tackle this issue. Here, this work formulates and illustrates a framework to guide development and assessment of the ML-based prognosis model for autonomous control systems. The development of the prognosis model considers the training of a ML model which consists of optimizing many aspects of the ML approach. The assessment of the prognosis model considers training data limitations and uncertainties of the ML approach. Prognosis models with standalone ML and PGML are developed and assessed on the loss-of-flow scenario of Experimental Breeder Reactor II. The results indicate that PGML based prognosis model has the best performance compared to other prognosis models.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2011

The Preflight Calibration of the Thermal Infrared Sensor (TIRS) on the Landsat Data Continuity Mission

The preflight calibration testing of TIRS evaluates the performance of the instrument at the component, subsystem and system level, The overall objective is to provide an instrument that is well calibrated and well characterized with specification compliant data that will ensure the data continuity of Landsat from the previous missions to the LDCM, The TIRS flight build unit and the flight instrument were assessed through a series of calibration tests at NASA Goddard Space Flight Center. Instrument-level requirements played a strong role in defining the test equipment and procedures used for the calibration in the thermal/vacuum chamber. The calibration ground support equipment (CGSE), manufactured by MEI and ATK Corporation, was used to measure the optical, radiometric and geometric characteristics of TIRS, The CGSE operates in three test configurations: GeoRad (geometric, radiometric and spatial), flood source and spectral, TIRS was evaluated though the following tests: bright target recovery, radiometry, spectral response, spatial shape, scatter, stray light, focus, and uniformity, Data were obtained for the instrument and various subsystems under conditions simulating those on orbit In the spectral configuration, a monochromator system with a blackbody source is used for in-band and out-of-band relative spectral response characterization, In the flood source configuration the entire focal plane array is illuminated simultaneously to investigate pixel-to-pixel uniformity and dead or inoperable pixels, The remaining tests were executed in the GeoRad configuration and use a NIST calibrated cavity blackbody source, The NIST calibration is transferred to the TIRS sensor and to the blackbody source on-board TIRS, The onboard calibrator will be the primary calibration source for the TIRS sensor on orbit.

Smith, Ramsey↗
NASA NTRS2016

A Fly-Through Mission Strategy Targeting Peptide as a Signature of Chemical Evolution and Possible Life in Enceladus Plumes

In situ detection of organic molecules in the extraterrestrial environment provides a key step towards better understanding the variety and the distribution of building blocks of life and it may ultimately lead to finding extraterrestrial life within the Solar System. Here we present combined results of two separate experiments that enable us to realize such in situ life signature detection from the deep habitats of the "Ocean World": a hydrothermal reactor experiment simulating complex organic synthesis and a simulated fly-through capture experiment of organic-bearing microparticles using silica aerogels, followed by subsequent analysis. Both experiments employ peptide as a plausible organics existing in Encleadus plume particles produced in its subsurface ocean. Recent laboratory hydrothermal experiments and a theoretical model on silica saturation indicated an on going hydrothermal reactions in subsurface Enceladus ocean. Given the porous chondritic origin of the core, it is likely that organic compounds originated by radiation chemistry such as amino acid precursors could have been provided, leached, and altered through widespread water-rock interactions. By using the same laboratory experimental setup from the latest water-rock interaction study, we performed amino acid polymerization experiments for 144 days and monitored the organic complexity changing over time. So far over 3,000 peaks up to the size of greater than 600 MW were observed through the analysis of capillary electrophoresis time-of-flight mass spectrometry (CE-TOF-MS) with an indication of amino acid derivatives and short peptides. Generally abiotic polymerization of enantiomeric amino acids results in forming stereoisomeric peptides with identical molecular weight and formula as opposed to homochiral biopolymers. Assuming Enceladus plume particles may contain a mixture of stereoisomeric peptides, we were able to distinguish 16 of the 17 stereoisomeric tripeptides as a test sample using capillary electrophoresis (CE) under optimized conditions. We further conducted Enceladus plume fly-through capture experiment by accelerating peptides soaked in rock particles up to a speed of 5.7 km/s and capturing with originally developed hydrophobic silica aerogels. Direct peptide extraction with acetonitrile-water followed by CE analysis led to detection of only but two stereoisomeric acidic peptide peaks, presenting the first run-through hypervelocuty impact sample analysis targeting peptides as key molecule to to understand the ongoing astrobiology on Enceladus.

organic molecules↗
DOE OSTI2022

Simulation of hydropower at subcontinental to global scales: a state-of-the-art review

Abstract Hydroelectric power is playing a new and often expanded role in the world’s major power grids, offering low carbon generating capacity in industrializing, dam-building economies while providing reserve and flexibility to co-manage fledgling wind and solar resources in high income countries. Driven by river flows, conventional hydropower is exposed to the vagaries of weather and climate, motivating drought and climate change hydropower impact studies at large spatial scales. Here we review methods of climate-driven hydropower simulation at large spatial scales, specifically multi-basin regions to global. We identify four types of approach based on complexity of tools and richness of data applied to the problem. Since the earliest attempts to model climate-driven hydropower at continental scale almost two decades ago, the field has transitioned from one of scientific curiosity to practical application, with studies increasingly motivated by the need to inform power grid expansion planning and operation. As the hydrological and water management models used in large-scale hydropower studies become more sophisticated, new opportunities will emerge to study the impacts of changing hydropower on power system reliability and performance at large power grid scale. To grasp these opportunities, the water resources community must continue to enhance data and models for representing river flows and anthropogenic water use and management at subcontinental to global scales.

13 HYDRO ENERGY↗
DOE OSTI2026

Stacked reverberation mapping of high-redshift quasars in DESI. I. Feasibility analysis

The broad-line region of quasars has long been probed by reverberation mapping techniques that measure time lags between continuum and broad emission-line variations. Stacked reverberation mapping has been proposed as a less observationally expensive alternative to traditional methods. This ensemble approach also reduces biases from small-number statistics. The Dark Energy Spectroscopic Instrument (DESI) is conducting the most extensive spectroscopic survey of quasars to date. We create mock light curves emulating expected DESI quasar observations at redshifts $1.48\lt z\lt 5.2$ and luminosities $44.68 \le \log \lambda L_{1350 \mathring{\rm A}{}} / \mathrm{erg\, s^{-1}} \le 45.99$ to test stacked reverberation mapping feasibility using sparse spectroscopic data paired with well-sampled photometric data. The pipeline, using the lag estimation code JAVELIN (Just Another Vehicle for Estimating Lags In Nuclei), successfully recovers the simulated C IV lags within 1σ of the true values using spectroscopic light curves composed of only a few spectral epochs (2–10) with irregular cadences. We investigate how observational factors, including C IV flux error magnitude, number of stacked quasars, and spectral epoch count, affect performance. This work motivates a pathway for future stacked reverberation mapping projects with large-scale spectroscopic surveys of quasars having $\ge 2$ spectroscopic observations. Our results suggest an economical alternative for constraining and extending the radius–luminosity relation to higher redshifts and luminosities. Subsequently, this relation can be employed more reliably in single-epoch black hole mass measurements and quasar cosmology in these distant regimes.

quasars: general, quasars: supermassive black hole↗
NASA NTRS2002

MDP: Reliable File Transfer for Space Missions

This paper presents work being done at NASA/GSFC by the Operating Missions as Nodes on the Internet (OMNI) project to demonstrate the application of the Multicast Dissemination Protocol (MDP) to space missions to reliably transfer files. This work builds on previous work by the OMNI project to apply Internet communication technologies to space communication. The goal of this effort is to provide an inexpensive, reliable, standard, and interoperable mechanism for transferring files in the space communication environment. Limited bandwidth, noise, delay, intermittent connectivity, link asymmetry, and one-way links are all possible issues for space missions. Although these are link-layer issues, they can have a profound effect on the performance of transport and application level protocols. MDP, a UDP-based reliable file transfer protocol, was designed for multicast environments which have to address these same issues, and it has done so successfully. Developed by the Naval Research Lab in the mid 1990's, MDP is now in daily use by both the US Post Office and the DoD. This paper describes the use of MDP to provide automated end-to-end data flow for space missions. It examines the results of a parametric study of MDP in a simulated space link environment and discusses the results in terms of their implications for space missions. Lessons learned are addressed, which suggest minor enhancements to the MDP user interface to add specific features for space mission requirements, such as dynamic control of data rate, and a checkpoint/resume capability. These are features that are provided for in the protocol, but are not implemented in the sample MDP application that was provided. A brief look is also taken at the status of standardization. A version of MDP known as NORM (Neck Oriented Reliable Multicast) is in the process of becoming an IETF standard.

Rash, James↗
NASA NTRS2014

A Flight Research Overview of WSPR, a Pilot Project for Sonic Boom Community Response

In support of the ongoing effort by the National Aeronautics and Space Administration (NASA) to bring supersonic commercial travel to the public, the NASA Armstrong Flight Research Center and the NASA Langley Research Center, in cooperation with other industry organizations, conducted a flight research experiment to identify the methods, tools, and best practices for a large-scale quiet (or low) sonic boom community human response test. The name of the effort was Waveforms and Sonic boom Perception and Response (WSPR). Such tests will be applied to building a dataset that governing agencies such as the Federal Aviation Administration and the International Civil Aviation Organization will use to establish regulations for acceptable sound levels of overland sonic booms. The WSPR test was the first such effort that studied responses to non-traditional low sonic booms while the subject persons were in their own homes and performing daily activities.The WSPR test was a NASA collaborative effort with several industry partners, in response to a NASA Aeronautics Research Mission Directorate Research Opportunities in Aeronautics. The primary contractor was Wyle (El Segundo, California). Other partners included Gulfstream Aerospace Corporation (Savannah, Georgia); Pennsylvania State University (University Park, Pennsylvania); Tetra Tech, Inc. (Pasadena, California); and Fidell Associates, Inc. (Woodland Hills, California).A major objective of the effort included exposing a community to the sonic boom magnitudes and occurrences that would be expected to occur in high-air traffic regions having a network of supersonic commercial aircraft in place. Low-level sonic booms designed to simulate those produced by the next generation of commercial supersonic aircraft were generated over a small residential community. The sonic boom footprint was recorded with an autonomous wireless microphone array that spanned the entire community. Human response data were collected using multiple survey methods. The research focused on essential elements of community response testing including subject recruitment, survey methods, instrumentation systems, flight planning and operations, and data analysis methods.This paper focuses on the NASA role in the logistics and operations of the effort, including human response subject recruitment, the operational processes involved in implementing the surveys throughout the community, instrumentation systems, logistics, flight planning, and flight operations. Findings discussed in this paper include critical lessons learned in all of the above-mentioned areas, as well as flight operations results. Analysis of the accuracy and repeatability of planning and executing the unique aircraft maneuver used to generate low sonic booms concluded that the sonic booms had overpressures within 0.15 lbft2 of the planned values for 76 percent of the attempts. Similarly, 90 percent of the attempts to generate low sonic booms within the community were successful.

community response↗
DOE OSTI2022

Expanded analysis of machine learning models for nuclear transient identification using TPOT

Industries around the world are becoming more and more data driven. The nuclear field is no exception with several different applications being proposed. One popular area of research is the use of machine learning in transient detection. This paper seeks to build upon a previous study which made use of the AutoML package TPOT to train traditional machine learning models to classify transient events occurring with a reactor. Synthetic data was once again collected using a GPWR reactor simulator. Data on 12 different events was collected using 15 different initial conditions. Here, a dataset consisting of over 100,000 data points was compiled and used to train 7 different machine learning models using a pre-defined TPOT dictionary with 12 different preprocessing techniques. Three of the trained models were able to produce validation results in the 90s with the expanded dataset. Once the models were trained, it was possible to look into where during the simulation, misclassifications occurred. Using these three models, analysis was done to determine if TPOT could be used to train models that were effective if important features were missing. The results from this were positive with the newly trained models scoring close to the original models. Finally, to conclude this study, the three high performing models were retrained using different random states to see if there was any major variation when different states were used.

42 ENGINEERING↗
DOE OSTI2023

Finding Your Niche: An Evolutionary Approach to HPC Topologies

Traditional interconnection network design approaches focus on building general network topologies by optimizing the bisection bandwidth or minimizing the network’s diameter to reduce the maximum distance between any two nodes, thus amortizing the overall execution time of the HPC workloads. While such network topologies may accommodate a wide variety of applications in general, this may result in sub-optimal performance for many frequently-executed or dynamic workloads. In this paper, instead of focusing on designing an all-encompassing, general-purpose network topology, we develop a methodology to design customized network interconnects, evolved by “finding” the optimal topologies for a particular target workload given by its communication and contention profiles. To this end, we implement a Genetic Algorithm (GA)-based approach for network topology design tailored to improve the overall execution time of a particular workload of interest. We conducted extensive experiments with well-known motifs in physics-based workloads (Sweep3D and FFT), as well as with a representative graph application (MiniVite), using the well-known Structural Simulation Toolkit (SST) Macroscale Element Library (SST/macro) simulator for network interconnect evaluation. We demonstrate that our genetic algorithm-based approach is robust enough to find the underlying optimal topology of a particular workload.

network interconnects, graph search, meta-heuristi↗
NASA NTRS1999

The Biolink Implantable Telemetry System

Most biotelemetry applications deal with the moderated data rates of biological signals. Few people have studied the problem of transcutaneous data transmission at the rates required by NASA's Life Sciences-Advanced BioTelemetry System (LS-ABTS). Implanted telemetry eliminate the problems associated with wire breaking the skin, and permits experiments with awake and unrestrained subjects. Our goal is to build a low-power 174-216MHz Radio Frequency (RF) transmitter suitable for short range biosensor and implantable use. The BioLink Implantable Telemetry System (BITS) is composed of three major units: an Analog Data Module (ADM), a Telemetry Transmitter Module (TTM), and a Command Receiver Module (CRM). BioLink incorporates novel low-power techniques to implement a monolithic digital RF transmitter operating at 100kbps, using quadrature phase shift keying (QPSK) modulation in the 174-216MHz ISM band. As the ADM will be specific for each application, we focused on solving the problems associated with a monolithic implementation of the TTM and CRM, and this is the emphasis of this report. A system architecture based on a Frequency-Locked Loop (FLL) Frequency Synthesizer is presented, and a novel differential frequency that eliminates the need for a frequency divider is also shown. A self sizing phase modulation scheme suitable for low power implementation was also developed. A full system-level simulation of the FLL was performed and loop filter parameters were determined. The implantable antenna has been designed, simulated and constructed. An implant package compatible with the ABTS requirements is also being proposed. Extensive work performed at 200MHz in 0.5um complementary metal oxide semiconductors (CMOS) showed the feasibility of integrating the RF transmitter circuits in a single chip. The Hajimiri phase noise model was used to optimize the Voltage Controlled Oscillator (VCO) for minimum power consumption. Two test chips were fabricated in a 0.5pm, 3V CMOS process. Measured phase noise for a 1.5mW, 200MHz ring oscillator VCO is -80dBc/Hz at 100KHZ offset, showing good agreement with the theory. We also propose a novel superregenerative receiver architecture for implementing the command receiver. The superregenerative receiver's simplicity, low cost, and low power consumption has made it the receiver of choice for short-distance data communications, remote control and home automation. We present the design of a superregenerative AM receiver implemented in a 0.5um CMOS technology that operates at 433.92MHz and dissipates only 300uW. Further work entails detailed transistor-level design of the FLL and superregenerative receiver and a monolithic implementation of an implantable transceiver in 0.5um CMOS technology.

Betancourt-Zamora, Rafael J.↗
DOE OSTI2025

Nature-inspired lotus-shaped fins combined with hybrid nanoparticles and metal foam for high-performance latent heat thermal energy storage

Latent heat thermal energy storage (LHTES) systems play a critical role in renewable energy integration by providing high energy density and nearly isothermal operation during phase transitions. However, their performance is often limited by slow melting/charging rates, which motivates the search for enhanced heat transfer designs. This study investigates the melting behavior of RT-82 phase change material (PCM) using novel lotus-shaped fins combined with copper metal foam and conductive graphene nanoparticles and carbon nanotubes. A two-dimensional enthalpy-porosity model in ANSYS Fluent was developed to simulate the charging/melting process, capturing non-thermal equilibrium between the foam and PCM/nano-PCM. In this study, effects of fin geometry, nanoparticle concentration, and foam porosity on melting dynamics and cost-performance trade-offs were investigated. Results showed that natural convection accelerated melting by ~12% compared to conduction-only scenarios. Optimized lotus-shaped fins with higher fin density (T3F4 and T3F10) achieved up to 63% faster melting relative to sparse configurations. Graphene nanoparticles improved thermal conductivity, with a 6% volume fraction, by reducing melting time by ~6.9%, while their combination with 75% porosity foam achieved a maximum reduction in the melting time of ~51% compared to pure PCM. Cost-performance analysis identified T3F4 as the most balanced design, offering rapid thermal response without excessive material costs, while moderate-density designs like T3S6 provided economical alternatives with acceptable performance. These results highlight the performance enhancement that can be achieved by integrating bio-inspired fins, nanoparticles, and foams, into compact and efficient LHTES for solar heating, building thermal management, and industrial waste-heat recovery applications.

25 ENERGY STORAGE↗
DOE OSTI2024

High-Throughput Computing: Case Study of Medical Image Processing Applications

HPC is designed for large-scale simulations using monolithic codes of tightly coupled processes highly optimized to deliver decreased time to solution. Medical image processing is not a traditional field of HPC. Similar to AI applications, medical image processing parses large datasets, typically multiple times, to support a variety of studies for classification, diagnosis or monitoring purposes. The convergence of AI, HPC and Big Data encouraged more fields using image processing to transition to HPC. However, not all applications benefit from the same optimizations. In this paper we focus on high throughput medical image processing applications that analyze a huge dataset of small MRI images and that require HPC systems to decrease the time of parsing the entire dataset and not individual MRIs. We show in this research the performance of running SLANT, an image processing application for a whole brain segmentation, on large-scale systems and highlight performance limitations. We present optimizations prioritizing throughput that exhibit a 3.5x speed-up on the Summit Supercomputer that can be used as a baseline for building a high-throughput execution framework for other HPC systems.

Predescu, Maria↗
NASA NTRS2002

MDP: Reliable File Transfer for Space Missions

This paper presents work being done at NASA/GSFC (Goddard Space Flight Center) by the Operating Missions as Nodes on the Internet (OMNI) project to demonstrate the application of the Multicast Dissemination Protocol (MDP) to space missions to reliably transfer files. This work builds on previous work by the OMNI project to apply Internet communication technologies to space communication. The goal of this effort is to provide an inexpensive, reliable, standard, and interoperable mechanism for transferring files in the space communication environment. Limited bandwidth, noise, delay, intermittent connectivity, link asymmetry, and one-way links are all possible issues for space missions. Although these are link-layer issues, they can have a profound effect on the performance of transport and application level protocols. MDP, a UDP (User Datagram Protocol)-based reliable file transfer protocol, was designed for multicast environments which have to address these same issues, and it has done so successfully. Developed by the Naval Research Lab in the mid 1990s, MDP is now in daily use by both the US Post Office and the DoD (Department of Defense). This paper describes the use of MDP to provide automated end-to-end data flow for space missions. It examines the results of a parametric study of MDP in a simulated space link environment and discusses the results in terms of their implications for space missions. Lessons learned are addressed, which suggest minor enhancements to the MDP user interface to add specific features for space mission requirements, such as dynamic control of data rate, and a checkpoint/resume capability. These are features that are provided for in the protocol, but are not implemented in the sample MDP application that was provided. A brief look is also taken at the status of standardization. A version of MDP known as NORM (Nack Oriented Reliable Multicast) is in the process of becoming an IETF (Internet Engineering Task Force) standard.

Rash, James↗
DOE OSTI2020

VENTSAR V3.0: A Python GUI for Estimating Contaminant Concentrations on or Near Buildings Due to Building Effects and Plume Rise and For Calculating Inhalation and Plume Shine Doses

VENTSAR: Originated as VENTAX (Smith and Weber 1983) on the IBM Mainframe at the Savannah River Site (SRS) as a Fortran program. Updated to VENTSAR XL V1.0 (Simpkins 1997) as a spreadsheet version using macros created in Microsoft Excel. Later updated to VENTSAR XL V2.0 (Dixon 2018) as a spreadsheet executing a modified version of the original VENTAX Fortran code. Estimates contaminant concentrations on or near a building from a release at a nearby location. Calculates concentrations for a given meteorological exceedance probability or for a given stability and wind speed combination. Can model a single building with or without a penthouse on top or a ground location from either a stack or ground release. Plume rise can be considered. Contaminant releases can be chemical or radioactive with downwind concentrations determined at user-specified distances. Wind passing over and around buildings creates a complicated dispersion pattern. Air-intake vents may be located on building roofs or near the ground downwind of a release source. An estimation of pollutant concentrations on or near a structure is important in determining expected pollutant levels. Meteorological data are selected based on a specific area of the site. Fortran-based VENTAX able to make fast, complex mathematical calculations. Not user-friendly VENTSAR XL V1.0 no longer supported due to obsolete Excel macros. VENTSAR XL V2.0 an interim solution using an Excel spreadsheet to interface with the modified VENTAX Fortran code. Requires user to have Microsoft Excel. Not an intuitive interface for someone unfamiliar with VENTSAR. Does not perform dose calculations. VENTSAR V3.0 goal to combine the strengths of previous versions of VENTSAR into a single, powerful yet user-friendly program with a Graphical User Interface (GUI). Not dependent upon a specific program or plug-ins. Self-contained package to be used on any computer running Microsoft Windows. User-friendly, intuitive GUI created in Python for parameter input. Executes same modified VENTAX Fortran code as VENTSAR XL V2.0. Outputs formatted text file of completed calculations for easy review and dissemination. Performs inhalation and plume shine dose calculations for up to 11 user-selected nuclides from a nuclide dose factor library of almost 500 nuclides. 12 test cases were created for verification of V1.0 and V2.0. Same test cases run in V3.0 to verify correct performance. V3.0 produced similar results to V1.0. Confirmed GUI did not alter calculations in any way. Comparisons of the test case results confirm the V3.0 GUI does not influence the VENTSAR calculations. Simply passes same input parameters to VENTAX Fortran code for execution. Provides end user an easy-to-use, intuitive tool to quickly make building effect and plume rise calculations, as well as, inhalation and plume shine dose calculations. No experience with or working knowledge of Fortran, Excel, command line, or macros required. Self-contained package allows VENTSAR be deployed to any Windows computer without the need for specific programs or plug-ins.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Learning-based CO 2 concentration prediction: Application to indoor air quality control using demand-controlled ventilation

There have been increasing concerns over the air quality inside buildings as high levels of bio-effluents can cause nausea, dizziness, headaches, and fatigue to the people working in those spaces. First published in 2004 as Standard 62.1, ASHRAE Standard 62.2-2019 requires highly occupied spaces to implement heating, ventilation, and air conditioning (HVAC) that can dilute contaminants produced by occupants. In this regard, occupant-centric ventilation control has been regarded as an effective practice to maintain a satisfactory indoor air quality (IAQ) when dealing with highly variable occupancy environments. However, few established models in current literature and practice consider dynamic occupancy behavior and adaptive IAQ control. To address this gap, a dynamic indoor CO2 model is constructed using machine learning algorithms to forecast CO2concentrations across a range of forecasting horizons. Herein, we tuned and compared six state-of-the-algorithms—including Support Vector Machine, Ada Boost, Random Forest, Gradient Boosting, Logistic Regression, and Multilayer Perceptron. The algorithms’ performances are validated using CO 2 and historical meteorological data collected from a campus classroom with a variable occupancy rate. Simulation results showed that Multilayer Perceptron can strongly predict the volatile CO 2 behavior and also outperforms other algorithms in terms of accuracy. Furthermore, a control strategy capable of modeling and detecting dynamic patterns of CO 2 level is utilized to modulate the ventilation rate in real-time and also reduce the energy consumption. The proposed controller reduced the HVAC fan’s energy consumption by 51.4% and provide ventilation as needed per the ASHRAE standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

BEEAM (Building Electrical Efficiency Analysis Model) [SWR-20-107]

Modern high-performance buildings exhibit an increasing number of building loads that use direct current (DC) electricity internally, rather than alternating current (AC), due to the advent of low-cost computing and advanced power electronics. Powering DC devices from the AC grid requires AC/DC power conversion, which introduces energy losses and reduces efficiency. As DC loads proliferate, the cumulative wasted energy associated with hundreds of millions of AC/DC converters has become one of the broadest energy savings opportunities in buildings. DC power distribution systems have been proposed as an elegant and transformative solution to the problem of DC devices. In a DC distribution system, the building's wires carry DC electricity, rather than AC; and a few centralized, highly efficient AC/DC converters replace the many smaller, less efficient converters that serve individual DC loads. Unfortunately, the trade-offs associated with DC distribution systems are not well understood. Reported energy savings associated with DC power distribution differ widely and have not been well validated. The Building Electrical Efficiency Analysis Model (BEEAM) is a Modelica library that simulates the efficiency of building electrical distribution systems using harmonic power flow. BEEAM can model a wide variety of building distribution topologies, including three-phase AC, single-phase AC, unipolar DC, bipolar DC, and hybrid networks under both balanced and unbalanced load conditions. BEEAM accurately models power electronic converter losses, provides granular estimates of losses throughout the distribution system, and properly models efficiency at part load conditions. Users can package BEEAM within a functional mockup unit (FMU), enabling co-simulation with other modeling platform, such as EnergyPlus. In summary, BEEAM provides a tool suite for fair and accurate comparison of the efficiency of building electrical distribution systems, including AC, DC, and hybrid systems.

Frank, Stephen↗
DOE OSTI2022

Provably accurate simulation of gauge theories and bosonic systems

Quantum many-body systems involving bosonic modes or gauge fields have infinite-dimensional local Hilbert spaces which must be truncated to perform simulations of real-time dynamics on classical or quantum computers. To analyze the truncation error, we develop methods for bounding the rate of growth of local quantum numbers such as the occupation number of a mode at a lattice site, or the electric field at a lattice link. Our approach applies to various models of bosons interacting with spins or fermions, and also to both abelian and non-abelian gauge theories. We show that if states in these models are truncated by imposing an upper limit Λ on each local quantum number, and if the initial state has low local quantum numbers, then an error at most ϵ can be achieved by choosing Λ to scale polylogarithmically with ϵ − 1 , an exponential improvement over previous bounds based on energy conservation. For the Hubbard-Holstein model, we numerically compute a bound on Λ that achieves accuracy ϵ , obtaining significantly improved estimates in various parameter regimes. We also establish a criterion for truncating the Hamiltonian with a provable guarantee on the accuracy of time evolution. Building on that result, we formulate quantum algorithms for dynamical simulation of lattice gauge theories and of models with bosonic modes; the gate complexity depends almost linearly on spacetime volume in the former case, and almost quadratically on time in the latter case. We establish a lower bound showing that there are systems involving bosons for which this quadratic scaling with time cannot be improved. By applying our result on the truncation error in time evolution, we also prove that spectrally isolated energy eigenstates can be approximated with accuracy ϵ by truncating local quantum numbers at Λ = polylog ( ϵ − 1 ) .

Tong, Yu↗