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All sources NASA NTRS DOE OSTI

DOE OSTI2024

Deep-Learning-Based Multi-Timescale Load Forecasting in Buildings: Opportunities and Challenges from Research to Deployment

Electricity load forecasting for buildings and campuses is becoming increasingly important as the penetration of distributed energy resources (DERs) grows. Efficient operation and dispatch of DERs require reasonably accurate predictions of future energy consumption in order to conduct near-real-time optimized dispatch of on-site generation and storage assets. Electric utilities have traditionally performed load forecasting for load pockets spanning large geographic areas, and therefore, forecasting has not been a common practice by buildings and campus operators. Given the growing trends of research and prototyping in the grid-interactive efficient buildings domain, characteristics beyond simple algorithm forecast accuracy are important in determining the algorithm's true utility for smart buildings. Other characteristics include the overall design of the deployed architecture and the operational efficiency of the forecasting system. In this work, we present a deep-learning-based load forecasting system that predicts the building load at 1-hour intervals for 18 hours in the future. We also discuss challenges associated with the real-time deployment of such systems as well as the research opportunities presented by a fully functional forecasting system that has been developed within the National Renewable Energy Laboratory's Intelligent Campus program.

building load forecasting↗

NASA NTRS1974

Hot and cold body reference noise generators from 0 to 40 GHz

This article describes the design, development, and analysis of exceptionally accurate radiometric noise generators from 0-40 GHz to serve as standard references. Size, weight, power, and reliability are optimized to meet the requirements of NASA air- and space-borne radiometers. The radiometric noise temperature of these noise generators is, unavoidably, calculated from measured values rather than measured directly. The absolute accuracy and stability are equal to or better than those of reliable standards available for comparison. A noise generator has been developed whose measurable properties (VSWR, line loss, thermometric temperatures) have been optimized in order to minimize the effects of the uncertainty in the calculated radiometric noise temperatures. Each measurable property is evaluated and analyzed to determine the effects of the uncertainty of the measured value. Unmeasurable properties (primarily temperature gradients) are analyzed, and reasonable precautions are designed into the noise generator to guarantee that the uncertainty of the value remains within tolerable limits.

Hornbostel, D. H.↗

DOE OSTI2024

CACTUS: Chemistry Agent Connecting Tool Usage to Science

Large language models (LLMs) have shown remarkable potential in various domains but often lack the ability to access and reason over domain-specific knowledge and tools. In this article, we introduce Chemistry Agent Connecting Tool-Usage to Science (CACTUS), an LLM-based agent that integrates existing cheminformatics tools to enable accurate and advanced reasoning and problem-solving in chemistry and molecular discovery. We evaluate the performance of CACTUS using a diverse set of open-source LLMs, including Gemma-7b, Falcon-7b, MPT-7b, Llama3-8b, and Mistral-7b, on a benchmark of thousands of chemistry questions. Our results demonstrate that CACTUS significantly outperforms baseline LLMs, with the Gemma-7b, Mistral-7b, and Llama3-8b models achieving the highest accuracy regardless of the prompting strategy used. Moreover, we explore the impact of domain-specific prompting and hardware configurations on model performance, highlighting the importance of prompt engineering and the potential for deploying smaller models on consumer-grade hardware without a significant loss in accuracy. By combining the cognitive capabilities of open-source LLMs with widely used domain-specific tools provided by RDKit, CACTUS can assist researchers in tasks such as molecular property prediction, similarity searching, and drug-likeness assessment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Three-dimensional cooperative inversion of airborne magnetic and gravity gradient data using deep-learning techniques

Using multiple geophysical methods has become a prevailing approach in numerous geophysical applications to investigate subsurface structures and parameters. These multimethod-based exploration strategies have the potential to greatly diminish uncertainties and ambiguities encountered during geophysical data analysis and interpretation. One of the applications is the cooperative inversion of airborne magnetic and gravity gradient data for the interpretation of data obtained in mineral, oil and gas, and geothermal explorations. In this paper, a unified cooperative inversion framework is designed by combining the standard separate inversions with a deep neural network (DNN), which serves as the link between different types of data. A well-trained DNN takes the separately inverted susceptibility and density models as the inputs and provides improved models that will be used as the initial models of deterministic inversions. A two-round iteration strategy is adopted to guarantee the reasonability of the recovered models and overall efficiency of the inversion. In addition, this deep-learning (DL)-based framework demonstrates excellent generalization abilities when tested on models that are entirely distinct from the training data sets. The framework can easily incorporate multiphysics without necessitating any structural changes to the network. Synthetic experiments validate that our DL-based method outperforms conventional separate inversions and cross-gradient-based joint inversion in view of the accuracy of the recovered models and inversion efficiency. Successful application to field data further verifies the effectiveness of our DL-based method.

Geochemistry & Geophysics↗

NASA NTRS1982

Some ideas and opportunities concerning three-dimensional wind-tunnel wall corrections

Opportunities for improving the accuracy and reliability of wall corrections in conventional ventilated test sections are presented. The approach encompasses state-of-the-art technology in transonic computational methods combined with the measurement of tunnel-wall pressures. The objective is to arrive at correction procedures of known, verifiable accuracy that are practical within a production testing environment. It is concluded that: accurate and reliable correction procedures can be developed for cruise-type aerodynamic testing for any wall configuration; passive walls can be optimized for minimal interference for cruise-type aerodynamic testing (tailored slots, variable open area ratio, etc.); monitoring and assessment of noncorrectable interference (buoyancy and curvature in a transonic stream) can be an integral part of a correction procedure; and reasonably good correction procedures can probably be developd for complex flows involving extensive separation and other unpredictable phenomena.

Rubbert, P. E.↗

NASA NTRS1984

Mean excitation energies for stopping powers in various materials using local plasma oscillator strengths

The basic model of Lindhard and Scharff, known as the local plasma model, is used to study the effects on stopping power of the chemical and physical state of the medium. Unlike previous work with the local plasma model, in which individual electron shifts in the plasma frequency were estimated empirically, he Pines correction derived for a degenerate Fermi gas is shown herein to provide a reasonable estimate, even on the atomic scale. Thus, the model is moved to a complete theoretical base requiring no empirical adjustments, as characteristic of past applications. The principal remaining error is in the overestimation of the low-energy absorption properties that are characteristic of the plasma model in the region of the atomic discrete spectrum, although higher-energy phenomena are accurately represented, and even excitation-to-ionization ratios are given to fair accuracy. Mean excitation energies for covalent-bonded gases and solids, for ionic gases and crystals, and for metals are calculated using first-order models of the bonded states.

Wilson, J. W.↗

NASA NTRS2012

SO2 over Central China: Measurements, Numerical Simulations and the Tropospheric Sulfur Budget

SO2 in central China was measured in situ from an aircraft and remotely using the Ozone Monitoring Instrument (OMI) from the Aura satellite; results were used to develop a numerical tool for evaluating the tropospheric sulfur budget - sources, sinks, transformation and transport. In April 2008, measured ambient SO2 concentrations decreased from approx.7 ppbv near the surface to approx. 1 ppbv at 1800 m altitude (an effective scale height of approx.800 m), but distinct SO2 plumes were observed between 1800 and 4500 m, the aircraft's ceiling. These free tropospheric plumes play a major role in the export of SO2 and in the accuracy of OMI retrievals. The mean SO2 column contents from aircraft measurements (0.73 DU, Dobson Units) and operational OMI SO2 products (0.63+/-0.26 DU) were close. The OMI retrievals were well correlated with in situ measurements (r = 0.84), but showed low bias (slope = 0.54). A new OMI retrieval algorithm was tested and showed improved agreement and bias (r = 0.87, slope = 0.86). The Community Multiscale Air Quality (CMAQ) model was used to simulate sulfur chemistry, exhibiting reasonable agreement (r = 0.62, slope = 1.33) with in situ SO2 columns. The mean CMAQ SO2 loading over central and eastern China was 54 kT, approx.30% more than the estimate from OMI SO2 products, 42 kT. These numerical simulations, constrained by observations, indicate that ",50% (35 to 61 %) of the anthropogenic sulfur emissions were transported downwind, and the overall lifetime of tropospheric SO2 was 38+/-7 h.

He, Hao↗

NASA NTRS2015

Lidar Measurements of Wind and Cloud Around Venus from an Orbiting or Floating/flying Platform

Given the presence of clouds and haze in the upper portion of the Venus atmosphere, it is reasonable to consider a Doppler wind lidar (DWL) for making remote measurements of the 3-dimensional winds within the tops of clouds and the overlying haze layer. Assuming an orbit altitude of 250 kilometers and cloud tops at 60 kilometers (within the upper cloud layer), an initial performance assessment of an orbiting DWL was made using a numerical instrument and atmospheres model developed for both Earth and Mars. It is reasonable to expect vertical profiles of the 3-dimensional wind speed with 1 kilometer vertical resolution and horizontal spacing of 25 kilometers to several 100 kilometers depending upon the desired integration times. These profiles would begin somewhere just below the tops of the highest clouds and extend into the overlying haze layer to some to-be-determined height. Getting multiple layers of cloud returns is also possible with no negative impact on velocity measurement accuracy. The knowledge and expertise for developing coherent Doppler wind lidar technologies and techniques, for Earth related mission at NASA Langley Research Center is being leveraged to develop an appropriate system suitable for wind measurement around Venus. We are considering a fiber-laser-based lidar system of high efficiency and smaller size and advancing the technology level to meet the requirements for DWL system for Venus from an orbiting or floating/flying platform. This presentation will describe the concept, simulation and technology development plan for wind and cloud measurements on Venus.

Singh, Upendra N.↗

NASA NTRSDate not supplied

Adaptive Learning for Reliability Analysis using Support Vector Machines

A novel algorithm is presented for adaptive learning of an unknown function that separates two regions of a domain.In the context of reliability analysis these two regions represent the failure domain, where a set of constraints or requirements are violated, and a safe domain where they are satisfied. The Limit State Function (LSF) separates these two regions. Evaluating the constraints for a given parameter point requires the evaluation of a computational model that may well be expensive. For this reason we wish to construct a meta-model that can estimate the LSFas accurately as possible, using only a limited amount of training data. This work presents an adaptive strategy employing a Support Vector Machine (SVM) as a meta-model to provide a semi-algebraic approximation of the LSF.We describe an optimization process that is used to select informative parameter points to add to training data at each iteration to improve the accuracy of this approximation. A formulation is introduced for bounding the predictions of the meta-model; in this way we seek to incorporate this aspect of Gaussian Process Models (GPMs) within anSVM meta-model. Finally, we apply our algorithm to two benchmark test cases, demonstrating performance that is comparable with, if not superior, to a standard technique for reliability analysis that employs GPMs

Adaptive learning↗

NASA NTRS1984

Development of a thermal environment simulator for large test articles in a vacuum

The simulation of the thermal environment by varying the effective sink temperature about the test article was examined. The accuracy of this simulation depends upon the spectral emissivity/absorptivity, the number and size of the control zones, the temperature of each zone, and the geometry of the enclosure. A very large number of zones closely conforming to the surface of the test article quickly become prohibitive due to expense and control problems. A two zone low price enclosure does not have the fidelity required for thermal balance testing. The development of a simulator which for a reasonable cost, simulates the thermal balance environment for most large test articles in the future is described.

Storrs, H. B.↗

NASA NTRS2016

Development of a High Performance, Low Profile Translation Table with Wire Feedthrough for a Deep Space CubeSat

NEAScout, a 6U cubesat and secondary payload on NASA's EM-1, will use an 85 sq m solar sail to travel to a near-earth asteroid at about 1 Astronomical Unit (about 1.5 x 10(exp 8) km) for observation and reconnaissance1. A combination of reaction wheels, reaction control system, and a slow rotisserie roll about the solar sail's normal axis were expected to handle attitude control and adjust for imperfections in the deployed sail during the 2.5-year mission. As the design for NEAScout matured, one of the critical design parameters, the offset in the center of mass and center of pressure (CP/CM offset), proved to be sub-optimal. After significant mission and control analysis, the CP/CM offset was accommodated by the addition of a new subsystem to NEAScout. This system, called the Active Mass Translator (AMT), would reside near the geometric center of NEAScout and adjust the CM by moving one portion of the flight system relative to the other. The AMT was given limited design space - 17 mm of the vehicle's assembly height-and was required to generate +/-8 cm by +/-2 cm translation to sub-millimeter accuracy. Furthermore, the design must accommodate a large wire bundle of small gage, single strand wire and coax cables fed through the center of the mechanism. The bend radius, bend resistance, and the exposure to deep space environment complicates the AMT design and operation and necessitated a unique design to mitigate risks of wire bundle damage, binding, and cold-welding during operation. This paper will outline the design constraints for the AMT, discuss the methods and reasoning for design, and identify the lessons learned through the designing, breadboarding and testing for the low-profile translation stages with wire feedthrough capability.

Few, Alex↗

NASA NTRS2016

Development of a High Performance, Low-Profile Translation Table with Wire Feedthrough

NEAScout, a 6U cubesat, will use an 85 sq m solar sail to travel to a near-earth asteroid for observation. Over the course of the 3-year mission, a combination of reaction wheels, cold gas reaction control system, and a slow rotisserie roll about the solar sail's normal axis were expected to handle attitude control and adjust for imperfections in the deployed sail. As the design for NEAScout matured, one of the critical design parameters, the offset in the center of mass and center of pressure (CP/CM offset), proved to be sub-optimal. After significant mission and control analysis, the CP/CM offset was addressed and a new subsystem was introduced to NEAScout. This system, called the Active Mass Translator (AMT), would reside near the geometric center of NEAScout and adjust the CM by moving one portion of the flight system relative to the other. The AMT was given limited design space-about 17 mm of the vehicle's assembly height-and was required to generate +/-10 cm by +/-5 cm translation to sub-millimeter accuracy. Furthermore, the design must accommodate a large wire bundle of small gage, single strand wire and coax cables fed through the center of the mechanism. The bend radius, bend resistance, and the exposure to deep space environment complicates the AMT design and operation and necessitated a unique design to mitigate risks of wire bundle damage, binding, and cold-welding during operation. This paper will outline the design constraints for the AMT, discuss the methods and reasoning for design, and identify the lessons learned through the design downselect process and breadboarding for designing low-profile translation stages with feedthrough capabilities.

Few, Alex↗

NASA NTRS2016

Development of a High-Performance, Low-Profile Translation Table with Wire Feedthrough for a Deep Space CubeSat

Few, Alex↗

DOE OSTI2021

Data-assisted combustion simulations with dynamic submodel assignment using random forests

This investigation outlines a data-assisted approach that employs random forest classifiers for local and dynamic submodel assignment in turbulent-combustion simulations. This method is demonstrated in simulations of a single-element GOX/GCH4 rocket combustor; a priori as well as a posteriori assessments are conducted to (i) evaluate the accuracy and adjustability of the classifier for targeting different quantities of interest (QoIs), and (ii) assess improvements, resulting from the data-assisted combustion model assignment, in predicting target QoIs during simulation runtime. Results from the a priori study show that random forests, trained with local flow properties as input variables and combustion model errors as training labels, assign three different combustion models – finite-rate chemistry (FRC), flamelet progress variable (FPV) model, and inert mixing (IM) – with reasonable classification performance even when targeting multiple QoIs. Applications in a posteriori studies demonstrate improved predictions from data-assisted simulations, in temperature and CO mass fraction, when compared with monolithic FPV calculations. An additional a posteriori data-assisted simulation of a modified configuration demonstrates that the present approach can be successfully applied to different configurations, as long as thermophysical behavior can be represented by the training data. Furthermore, these results demonstrate that this data-driven framework holds promise for dynamic combustion submodel assignments in reacting flow simulations.

42 ENGINEERING↗

DOE OSTI2020

Realistic Ion Dynamics through Charge Renormalization in Nonaqueous Electrolytes

While many practically important electrolytes contain lithium ions, interactions of these ions are particularly difficult to probe experimentally because of their small X-ray and neutron scattering cross sections and large neutron absorption cross sections. Molecular dynamics (MD) is a powerful tool for understanding the properties of nonaqueous electrolyte solutions from the atomic level, but the accuracy of this computational method crucially depends on the physics built into the classical force field. In this study, we demonstrate that several force fields for lithium bistriflimide (LiTFSI) in acetonitrile yield a solution structure that is consistent with the neutron scattering experiments, yet these models produce dramatically different ion dynamics in solution. Such glaring discrepancies indicate that inadequate representation of long-range interactions leads to excessive ionic association and ion-pair clustering. We show that reasonable agreement with the experimental observations can be achieved by renormalization of the ion charges using a “titration” method suggested herewith. This simple modification produces realistic concentration dependencies for ionic diffusion and conductivity in <2 M solutions, without loss in quality for simulation of the structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2014

Loads and Structural Dynamics Requirements for Spaceflight Hardware

The purpose of this document is to establish requirements relating to the loads and structural dynamics technical discipline for NASA and commercial spaceflight launch vehicle and spacecraft hardware. Requirements are defined for the development of structural design loads and recommendations regarding methodologies and practices for the conduct of load analyses are provided. As such, this document represents an implementation of NASA STD-5002. Requirements are also defined for structural mathematical model development and verification to ensure sufficient accuracy of predicted responses. Finally, requirements for model/data delivery and exchange are specified to facilitate interactions between Launch Vehicle Providers (LVPs), Spacecraft Providers (SCPs), and the NASA Technical Authority (TA) providing insight/oversight and serving in the Independent Verification and Validation role. In addition to the analysis-related requirements described above, a set of requirements are established concerning coupling phenomena or other interaction between structural dynamics and aerodynamic environments or control or propulsion system elements. Such requirements may reasonably be considered structure or control system design criteria, since good engineering practice dictates consideration of and/or elimination of the identified conditions in the development of those subsystems. The requirements are included here, however, to ensure that such considerations are captured in the design space for launch vehicles (LV), spacecraft (SC) and the Launch Abort Vehicle (LAV). The requirements in this document are focused on analyses to be performed to develop data needed to support structural verification. As described in JSC 65828, Structural Design Requirements and Factors of Safety for Spaceflight Hardware, implementation of the structural verification requirements is expected to be described in a Structural Verification Plan (SVP), which should describe the verification of each structural item for the applicable requirements. The requirement for and expected contents of the SVP are defined in JSC 65828. The SVP may also document unique verifications that meet or exceed these requirements with Technical Authority approval.

George James↗

NASA NTRS2016

The Impact of Truth Surrogate Variance on Quality Assessment/Assurance in Wind Tunnel Testing

Minimum data volume requirements for wind tunnel testing are reviewed and shown to depend on error tolerance, response model complexity, random error variance in the measurement environment, and maximum acceptable levels of inference error risk. Distinctions are made between such related concepts as quality assurance and quality assessment in response surface modeling, as well as between precision and accuracy. Earlier research on the scaling of wind tunnel tests is extended to account for variance in the truth surrogates used at confirmation sites in the design space to validate proposed response models. A model adequacy metric is presented that represents the fraction of the design space within which model predictions can be expected to satisfy prescribed quality specifications. The impact of inference error on the assessment of response model residuals is reviewed. The number of sites where reasonably well-fitted response models actually predict inadequately is shown to be considerably less than the number of sites where residuals are out of tolerance. The significance of such inference error effects on common response model assessment strategies is examined.

DeLoach, Richard↗

DOE OSTI2021

Analytics-at-scale of Sensor Data for Digital Monitoring in Nuclear Plants: 2nd Annual Report

For economic reasons, the nuclear industry is witnessing premature closure of nuclear power plants, despite excellent safety records. Operations and Maintenance (O&M) activities are some of the largest costs in operating legacy light-water plants. By reducing O&M costs, nuclear energy can become more economically competitive with other energy sources. This can be achieved by leveraging machine-learning and artificial intelligence technologies to develop data-driven algorithms to better diagnose potential faults within the system. Improved accuracy of the models can lead to a reduction in unnecessary maintenance, thus reducing costs associated with parts, labor, and unnecessary planned, forced, or extended outages. To address these challenges, the goal of this project is to perform research and development in the area of digital monitoring, i.e., the application of advanced sensor technologies (particularly wireless sensor technologies) and data science based analytic capabilities, to advance online monitoring and predictive maintenance in nuclear plants and improve plant performance (efficiency gain and economic competitiveness). This report summarizes the fiscal year 2020 research progress encompassing (1) different wireless vibration sensor and data indicators used to assess the health of a plant asset; (2) development of diagnostic models for fault detection; and (3) development of prognostic models for estimating the health of the system up to 7 days ahead.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗