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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Evaluation of Communication Issues in Primal-Dual-Based Distributed Energy Resource Management Systems (DERMS)

With the increasing adoption of distributed energy resources (DERs) in distribution networks, DERMS is becoming an attractive option to coordinate the control of DERs, especially primal-dual-based DERMS which is a well-developed class of them. In order to help lower the uncertainty in commercializing them, we evaluate and find the upper limits of severity for some common issues that can occur within the communication systems on which a primal-dual-based DERMS relies on; these include packet losses, link failures, and delays. This information can help a DERMS operator decide on the specifications for the communication infrastructure it will invest in for the DERMS. Our evaluation is based on numerical simulations of a real-world feeder with around 2,000 nodes and a DERMS that controls 163 PV generators and 140 energy storage batteries. In general, we found that the DERMS becomes less resistant to communication issues as the information flows closer to the DERs implementing the controllable power injections.

communication delay↗
DOE OSTI2023

Automating the Solar Interconnection Technical Evaluation Process: PREconfiguring and Controlling Inverter SEt-Points (PRECISE)

Utilities are receiving an increasing number of interconnection requests for distributed solar photovoltaic (PV) systems from their customers, requiring a solution to quickly and intelligently perform technical assessments of these requests and to manage these new renewable energy assets. In this paper, we present a stand-alone interconnection tool, PREconfiguring and Controlling Inverter SEt-points (PRECISETM), and how it overcomes the challenges of accelerating technical evaluations and leverages smart inverter functionality to provide local voltage support on an as-needed basis. The paper details the purpose and architecture of PRECISE, including tools, data source requirements, the model-based interconnection evaluation process, and technical results. PRECISE is an integrated software tool that customizes PV inverter settings for utilities by modeling and assessing impacts on local voltages and the need for advanced inverter functions (AIFs) (e.g., volt-VAR and volt-watt). PRECISE maximizes the use of readily available utility data sets to make fast online assessments of incoming PV interconnection requests and makes accept/reject recommendations along with custom settings for AIFs.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗
DOE OSTI2024

A Hierarchical OPF Algorithm with Improved Gradient Evaluation in Three-Phase Networks

Linear approximation commonly used in solving alternating-current optimal power flow (AC-OPF) simplifies the system models but incurs accumulated voltage errors in large power networks. Such errors will make the primal-dual type gradient algorithms converge to solutions with voltage violation. In this paper, we improve a recent hierarchical OPF algorithm that rested on primal-dual gradients evaluated with a linearized distribution power flow model. Specifically, we propose a more accurate gradient evaluation method based on an unbalanced three-phase nonlinear distribution power flow model to mitigate the errors arising from linearization. The resultant gradients feature a blocked structure that enables our development of an improved hierarchical primal-dual algorithm to solve the OPF problem. Numerical results on the IEEE 123-bus test feeder and a 4,518-node test feeder show that the proposed method can enhance voltage safety at comparable computational efficiency with the linearized algorithm.

approximation algorithms↗
DOE OSTI2020

Evaluation and Demonstration of Blockchain Applicability Framework

Blockchain technology has been gaining great interest from a variety of industry sectors, including financial, food processing, and power and energy markets. Realizing the strength of blockchain technology beyond the successful application in the cryptocurrency arena, researchers have been evaluating and using blockchain for applications such as supply chain management, transactive industry (both financial and energy), system integrity, device cybersecurity, identity management, and much more. One of the unique elements of the blockchain technology that made it such a captivating technology to researchers is its plethora of features. Some of the features include smart contracts, cryptocurrency and tokenizing, immutable distributed ledger, cryptographic hashing, and digital signature. In addition, there are multiple types of blockchains, such as permissioned/private and permissionless/public, and various consensus models, such as proof-of-work, proof-of-authority, proof-of-burn, and proof-of-stake. Therefore, it is often non-trivial to determine if an application requires a blockchain. If so, what kind of blockchain and consensus is most appropriate? This paper discusses the blockchain applicability framework (BAF), which was specifically designed with the purpose to answer those questions. BAF is divided into five domains, 18 subdomains, and about 100 controls. It is designed to ingest detailed user requirements to perform a weighted evaluation that is built on mathematical constructs to determine the ideal combination of blockchain that is appropriate for an application. Along with the core logical formulation of BAF, this paper depicts the efficacy of BAF through two use cases

Gourisetti, Sri Nikhil G.↗
DOE OSTI2025

A Polar Scaling Technique for the Regularization of Strongly Singular and Strongly Near-Singular Helmholtz Surface Integrals Evaluated Over 2-D Domains

The numerical integration of expressions containing strong singularities or strong near-singularities has long been a challenging problem in the electromagnetics community. Much attention has been paid to this problem, as strong $1/R^{{2}}$ singularities routinely appear when implementing electromagnetic simulation techniques like the method of moments (MoM). To date, several techniques, from singularity extraction to singularity cancellation (SC), have been employed to deal with problems that require the evaluation of 2-D strongly singular integrals. However, no single technique has been proposed that can deal with both strong singularities and strong near-singularities in a fully numerical manner for arbitrary 2-D domains. Moreover, it has been claimed that the Helmholtz-type strongly singular integral found in the MoM is convergent in a principal value sense, but this convergence value has yet to be proven mathematically. In this work, we will conduct the convergence proof and introduce a “polar scaling” change of variables method that may be used to evaluate Helmholtz integrals with both strong and weak singularities/near-singularities. The technique is fully numerical and can in principle be applied to any planar or curved polygon and any nonsingular basis function. We will also provide numerical results showing useful convergence behavior for integrals involving both exact and near-singularities.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication.

There is a growing interest in custom spatial accelerators for machine learning applications. These accelerators employ a spatial array of processing elements (PEs) interacting via custom buffer hierarchies and networks-on-chip. The efficiency of these accelerators comes from employing optimized dataflow (i.e., spatial/temporal partitioning of data across the PEs and fine-grained scheduling) strategies to optimize data reuse. The focus of this work is to evaluate these accelerator architectures using a tiled general matrix-matrix multiplication (GEMM) kernel. To do so, we develop a framework that finds optimized mappings (dataflow and tile sizes) for a tiled GEMM for a given spatial accelerator and workload combination, leveraging an analytical cost model for runtime and energy. Finally, our evaluations over five spatial accelerators demonstrate that the tiled GEMM mappings systematically generated by our framework achieve high performance on various GEMM workloads and accelerators.

42 ENGINEERING↗
DOE OSTI2021

A Machine Learning-based Reliability Evaluation Model for Integrated Power-Gas Systems

This article proposes a hybrid machine learning method for the reliability evaluation of integrated power-gas systems (IPGS) under the uncertain component failure probability distributions. The Random Forest (RF) method is designed to select important features to solve the insufficient quantity of data and the curse of dimensionality problems. The Extreme Gradient Boosting (XGBoost) regression algorithm is developed to quantify the relationship between the uncertain parameters and reliability metrics. Moreover, a ten-fold cross-validation method is employed to further improve the accuracy of the regression model. Simulation results on three test systems show that the proposed method can achieve high accuracy for the reliability evaluation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Evaluation of Aggregated EV Flexibility With TSO-DSO Coordination

Electric vehicles (EVs) are becoming a promising source of grid ancillary services due to the temporal and spatial charging flexibility, quick response and storage capability. Such advantages are increasing with government policy promotion and technology improvement. However, the exploration of EV flexibility requires the coordination of both transmission system operators (TSOs) and distribution system operators (DSOs), to ensure the safe and reliable operation of power network. In this paper, we propose a coordinated evaluation method that determines the optimal utilization of EV temporal flexibility without compromising EV owners’ usage. At the distribution level, DSOs first evaluate EV aggregators’ operational boundaries to exploit distribution level services. At the transmission level, TSOs then determine EV charging schedules and ancillary service capacity simultaneously, taking into account the requirement from DSOs. Here, we validate the model in a case study using the IEEE 123 node test feeder and EV charging sessions obtained from a transportation simulation tool that uses real-world data.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Evaluating generative networks using Gaussian mixtures of image features

We develop a measure for evaluating the performance of generative networks given two sets of images. A popular performance measure currently used to do this is the Fréchet Inception Distance (FID). However, FID assumes that images featurized using the penultimate layer of Inception follow a Gaussian distribution. This assumption allows FID to be easily computed, since FID uses the 2-Wasserstein distance of two Gaussian distributions fitted to the featurized images. However, we show that Inception features of the ImageNet dataset are not Gaussian; in particular, each marginal is not Gaussian. To remedy this problem, we model the featurized images using Gaussian mixture models (GMMs) and compute the 2-Wasserstein distance restricted to GMMs. We define a performance measure, which we call WaM, on two sets of images by using inception (or another classifier) to featurize the images, estimate two GMMs, and use the restricted 2-Wasserstein distance to compare the GMMs. We experimentally show the advantages of WaM over FID, including how FID is more sensitive than WaM to image perturbations. By modelling the non-Gaussian features obtained from inception as GMMs and using a GMM metric, we can more accurately evaluate generative network performance.

machine learning, genrative adversarial networks↗
DOE OSTI2023

Evaluation of eastern gamagrass as dual-purpose complementary bioenergy and forage feedstock to switchgrass

Switchgrass (SG) is considered a model bioenergy crop and a warm-season perennial grass (WSPG) that traditionally served as forage feedstock in the United States. To avoid the sole dependence on SG for bioenergy production, evaluation of other crops to diversify the pool of feedstock is needed. We conducted a 3-year field experiment evaluating eastern gamagrass (GG), another WSPG, as complementary feedstock to SG in one- and two-cut systems, with or without intercropping with crimson clover or hairy vetch, and under different nitrogen (N) application rates. Our results showed that GG generally produced lower biomass (by 29.5%), theoretical ethanol potential (TEP, by 2.8%), and theoretical ethanol yield (TEY, by 32.9%) than corresponding SG under the same conditions. However, forage quality measures, namely acid detergent fiber (ADF), crude protein (CP), and elements P, K, Ca, and Mg were significantly higher in GG than those in SG. Nitrogen fertilizer significantly enhanced biomass (by 1.54 Mg ha -1 ), lignin content (by 2.10 g kg -1 ), and TEY (787.12 L ha -1 ) in the WSPGs compared to unfertilized treatments. Intercropping with crimson clover or hairy vetch did not significantly increase biomass of the WSPGs, or TEP and TEY in unfertilized plots. This study demonstrated that GG can serve as a complementary crop to SG and could be used as a dual-purpose crop for bioenergy and forage feedstock in farmers' rotations.

09 BIOMASS FUELS↗
DOE OSTI2021

Evaluation of nutrient bioextraction by seaweed and shellfish aquaculture in Korea

Abstract Although Korea is third in seaweed production and second in shellfish production globally, this is the first study evaluating ecosystem services of seaweed and shellfish aquaculture in Korea. The objective of this study is to evaluate nutrient bioextraction capacities of major seaweed and shellfish species aquacultured in Korea. C (C) removal of three major aquacultured seaweed species, Neopyropia yezoensis , Saccharina japonica , and Undaria pinnatifida were 24,247, 8,423, and 12,758 tons, respectively, in 2016. N (N) removal of these species was 4,088, 732, and 1,244 tons, respectively. The C and N removal of the Pacific oysters ( Crassostrea gigas ) were 14,693 and 1,050 tons, respectively. Manila clams ( Venerupis philippinarum ) removed 2,120 tons of C and 136.5 tons of N. Together, 161,846 tons of CO 2 and 7,251 tons of N were removed by three major seaweed species and two shellfish species. These values are significant amounts, equivalent to 5.7% of CO 2 and 8.6% of N discharged from all wastewater treatment plants in Korea. These results suggest that nutrient bioextraction by aquacultured seaweed and shellfish can be a cost efficient, affordable, and equitable solution for coastal nutrient management programs in Korea and elsewhere.

Park, Ji‐Sook↗
DOE OSTI2020

Experimental Evaluation of Geopolymer, Nano-Modified, and Neat Class H Cement by Using Diametrically Compressive Tests

Abstract Cement is the prime barrier material to maintain zonal isolation during wellbore life-cycle. Different types of the cement have different performances on sealability. The primary objective of this study is evaluation of three types of cement systems, neat Class H, nano-synthetic graphite, and rock-based geopolymer cements, on interfacial bond integrity. Diametrical compressive tests are used on casing–cement–formation systems. Cement performances are tested in a conventional configuration (Berea Sandstone). A universal testing system is utilized to analyze the relationship applied load–axial strain and the digital image correlation (DIC) technique is used to generate the strain field maps. Based on the relationship and DIC results, bond strengths in different cement systems are evaluated. Additionally, microscope images provide insight explanations of the bond from micro-view. Based on the experimental results, failures of all cases initiate and propagate from the casing–cement interface. Then, radial cracks develop through the formation. This is because the mechanical interlocking bonds are formed only at the cement–sandstone interface to enhance the bond strength. The comparison of geopolymer and nano-modified cements with the conventional cement (neat Class H) shows that the unconventional cements have a lower maximum load and higher axial strain before failure of the samples. It indicates that both the two kinds of cements are more ductile than conventional cement and can support more deformation before the initiation of cracks.

Energy & Fuels↗
DOE OSTI2023

Critical Evaluation of a Novel Analysis Technique for Assessment of Printed Circuit Heat Exchangers in High-Temperature Nuclear Service

Application of printed circuit heat exchangers (PCHEs) to very high-temperature reactors (VHTRs) requires mechanical performance assessment methodologies. The PCHE morphology consists of thousands of millimeter-scale channels, for enhanced thermal efficiency, enclosed in a meter-scale PCHE core. PCHE geometry under thermomechanical creep-fatigue transients results in multi-axial interactions between its different segments, such as channeled core, walls, and headers. These global-level interactions influence the local channel-level responses. Hence, developing a PCHE performance assessment methodology, following the ASME Code, Section III, Division 5 provisions, is a critical gap to be filled. There is no analysis or design methodology available in ASME Code to assess a PCHE for its global and local level performances under high temperature and pressure loadings. This paper critically evaluates a recently proposed two-step analysis technique to estimate global interactions and local channel-level responses of PCHEs. In this novel analysis technique, the channeled PCHE core is replaced with orthotropic solid blocks of representative stiffness properties for the global thermomechanical analysis. Here, subsequent channel scale submodel analysis with detailed channel geometry, loading, and elastic-perfectly plastic (EPP) material model estimates the local responses for PCHE performance assessment. This paper critically evaluates this novel technique for its effectiveness in PCHE performance assessment. Finite element (FE) models imitating various analysis issues are developed, and FE analysis results are scrutinized. An important outcome of this study is the validation of the novel two-step PCHE analysis technique for application to the performance assessment of PCHEs in VHTRs.

42 ENGINEERING↗
DOE OSTI2022

MECHANICAL PERFORMANCE EVALUATION OF THE PRINTED CIRCUIT HEAT EXCHANGER CORE EXPERIMENTS UNDER TENSION AND PRESSURE LOADING

The printed circuit heat exchanger (PCHE) has small channels with high surface area, making them an efficient solution for next-generation nuclear plants (NGNPs). These PCHEs are fabricated through a diffusion bonding process. This fabrication step changes the microstructure of wrought metal plates. The current ASME design code does not support the PCHE design for NGNPs due to a lack of test data. Hence, there has been initiative towards elevated temperature mechanical property characterization of the diffusion bonded material. One of the most common channel shapes is a semicircular channel with sharp corners. These corners act as a stress riser at the diffusion bonding interface. Evaluating elevated temperature mechanical performance of diffusion bonded material in the presence of stress risers is an essential step towards the ASME code development of PCHE design. This study selected two specimen geometries: the first is a PCHE bar specimen for tensile loading with three rows and three columns of channels, and the second is a lab-scaled PCHE with six rows and eight columns of channels. A set of elevated temperature monotonic and cyclic tests were conducted on the PCHE bar specimen to evaluate the mechanical performance under axial tensile loadings to study the failure mechanism. The lab-scaled PCHE specimens were tested under overpressure loads at room temperature, and pressure creep and pressure creep-fatigue loadings to mimic the realistic loading conditions observed in typical NGNPs. The X-ray scans of channeled specimens show interesting observations. The test results and observations are presented in the paper.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Evaluation of Common Thermoplastic Polymers in High-Pressure Cycling Hydrogen Under Ambient and Cold Environments as Applicable to the Hydrogen Infrastructure

Thermoplastic polymers are required to perform unfailingly under stringent conditions of changing pressures (35 MPa to 70 MPa) and temperatures (-40°C to +85°C) in storage and fueling operations. Although diffusivity in glassy polymers appear to be an order of magnitude lower than elastomers, polymer microstructural attributes such as degree of crystallinity and presence of polar and non-polar groups on the main chain with and without branching can play a substantial role in influencing their behaviors in hydrogen environments. In the work described here, the effect of high-pressure hydrogen cycling on PEEK, PTFE, PA11, HDPE, POM (and different commercial grades of these polymers) under ambient and cold (-40°C) conditions is addressed. Ex-situ characterization for polymer changes included density measurements for impact of hydrogen retention, hardness changes using nanoindentation, storage modulus and glass transition changes using dynamic mechanical and thermal analysis (DMTA), degree of crystallization with Differential Scanning Calorimetry (DSC) and tensile testing following ASTM D412. In other evaluations, solid-state nuclear magnetic resonance (NMR), attenuated total reflectance Fourier transform infra-red spectroscopy (ATRFTIR), X-ray diffraction (XRD), and X-ray CT results are presented. The overall impact of these evaluations is to establish a technical basis for the behaviors of common thermoplastics in cycling hydrogen environments under ambient and cold temperatures while establishing the relationship between polymer structure-based properties and hydrogen transport effects.

Menon, Nalini C.↗
DOE OSTI2021

Evaluation of the accuracy of stopping and range of ions in matter simulations through secondary ion mass spectrometry and Rutherford backscattering spectrometry for low energy heavy ion implantation

The freely available “Stopping and Range of Ions in Matter” (SRIM) code is used for evaluating ion beam ranges and depth profiles. We present secondary ion mass spectrometry and Rutherford backscattering experimental results of Si samples implanted with low energy Sb ions to evaluate the accuracy of SRIM simulations. We show that the SRIM simulation systematically overestimates the range by 2–6 nm and this overestimation increases for larger ion implantation energy. For the lowest energy implantation investigated, here we find up to a 25% error between the SRIM simulation and the measured range. Finally, the ion straggle shows excellent agreement between simulation and experimental results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Evaluation of Immunocompetent Mouse Models for Borrelia miyamotoi Infection

Borrelia miyamotoi is a relapsing fever spirochete that is harbored by Ixodes spp. ticks and is virtually uncharacterized, compared to other relapsing fever Borrelia vectored by Ornithodoros spp. ticks. There is not an immunocompetent mouse model for studying B. miyamotoi infection in vivo or for transmission in the vector-host cycle. Our goal was to evaluate B. miyamotoi infections in multiple mouse breeds/strains as a prelude to the ascertainment of the best experimental infection model. Two B. miyamotoi strains, namely, LB-2001 and CT13-2396, as well as three mouse models, namely, CD-1, C3H/HeJ, and BALB/c, were evaluated. We were unable to observe B. miyamotoi LB-2001 spirochetes in the blood via darkfield microscopy or to detect DNA via real-time PCR post needle inoculation in the CD-1 and C3H/HeJ mice. However, LB-2001 DNA was detected via real-time PCR in the blood of the BALB/c mice after needle inoculation, although spirochetes were not observed via microscopy. CD-1, C3H/HeJ, and BALB/c mice generated an antibody response to B. miyamotoi LB-2001 following needle inoculation, but established infections were not detected, and the I. scapularis larvae failed to acquire spirochetes from the exposed CD-1 mice. In contrast, B. miyamotoi CT13-2396 was visualized in the blood of the CD-1 and C3H/HeJ mice via darkfield microscopy and detected by real-time PCR post needle inoculation. Both mouse strains seroconverted. However, no established infection was detected in the mouse organs, and the I. scapularis larvae failed to acquire Borrelia after feeding on CT13-2396 exposed CD-1 or C3H/HeJ mice. Furthermore, these findings underscore the challenges in establishing an experimental B. miyamotoi infection model in immunocompetent laboratory mice.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Beyond the Hype: An Evaluation of Commercially Available Machine-Learning-Based Malware Detectors

There is a lack of scientific testing of commercially available malware detectors, especially those that boast accurate classification of never-before-seen (i.e., zero-day) files using machine learning (ML). Consequently, efficacy of malware detectors is opaque, inhibiting end users from making informed decisions and researchers from targeting gaps in current detectors. In this paper, we present a scientific evaluation of four prominent commercial malware detection tools to assist an organization with two primary questions: To what extent do ML-based tools accurately classify previously and never-before-seen files? Is purchasing a network-level malware detector worth the cost? To investigate, we tested each tool against 3,536 total files (2,554 or 72% malicious, 982 or 28% benign) of a variety of file types, including hundreds of malicious zero-days, polyglots, and APT-style files, delivered on multiple protocols. We present statistical results on detection time and accuracy, consider complementary analysis (using multiple tools together), and provide two novel applications of the recent cost-benefit evaluation procedure of Iannacone & Bridges. Although the ML-based tools are more effective at detecting zero-day files and executables, the signature-based tool might still be an overall better option. Both network-based tools provide substantial (simulated) savings when paired with either host tool, yet both show poor detection rates on protocols other than HTTP or SMTP. Our results show that all four tools have near-perfect precision but alarmingly low recall, especially on file types other than executables and office files—37% of malware, including all polyglot files, were undetected. Priorities for researchers and takeaways for end users are given. Code for future use of the cost model is provided.

97 MATHEMATICS AND COMPUTING↗