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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Development of a GPU-based high-performance radiative transfer model for the Infrared Atmospheric Sounding Interferometer (IASI)

Satellite-observed radiance is a nonlinear functional of surface properties and atmospheric temperature and absorbing gas profiles as described by the radiative transfer equation (RTE). In the era of hyperspectral sounders with thousands of high-resolution channels, the computation of the radiative transfer model becomes more time-consuming. The radiative transfer model performance in operational numerical weather prediction systems still limits the number of channels we can use in hyperspectral sounders to only a few hundreds. To take the full advantage of such high-resolution infrared observations, a computationally efficient radiative transfer model is needed to facilitate satellite data assimilation. In recent years the programmable commodity graphics processing unit (GPU) has evolved into a highly parallel, multi-threaded, many-core processor with tremendous computational speed and very high memory bandwidth. The radiative transfer model is very suitable for the GPU implementation to take advantage of the hardware's efficiency and parallelism where radiances of many channels can be calculated in parallel in GPUs. In this paper, we develop a GPU-based high-performance radiative transfer model for the Infrared Atmospheric Sounding Interferometer (IASI) launched in 2006 onboard the first European meteorological polar-orbiting satellites, METOP-A. Each IASI spectrum has 8461 spectral channels. The IASI radiative transfer model consists of three modules. The first module for computing the regression predictors takes less than 0.004% of CPU time, while the second module for transmittance computation and the third module for radiance computation take approximately 92.5% and 7.5%, respectively. Our GPU-based IASI radiative transfer model is developed to run on a low-cost personal supercomputer with four GPUs with total 960 compute cores, delivering near 4 TFlops theoretical peak performance. By massively parallelizing the second and third modules, we reached 364x speedup for 1 GPU and 1455x speedup for all 4 GPUs, both with respect to the original CPU-based single-threaded Fortran code with the -O{sub 2} compiling optimization. The significant 1455x speedup using a computer with four GPUs means that the proposed GPU-based high-performance forward model is able to compute one day's amount of 1,296,000 IASI spectra within nearly 10 min, whereas the original single CPU-based version will impractically take more than 10 days. This model runs over 80% of the theoretical memory bandwidth with asynchronous data transfer. A novel CPU-GPU pipeline implementation of the IASI radiative transfer model is proposed. The GPU-based high-performance IASI radiative transfer model is suitable for the assimilation of the IASI radiance observations into the operational numerical weather forecast model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Solution to PDEs using radial basis function finite-differences (RBF-FD) on multiple GPUs

This paper presents parallelization strategies for the radial basis function-finite difference (RBF-FD) method. As a generalized finite differencing scheme, the RBF-FD method functions without the need for underlying meshes to structure nodes. It offers high-order accuracy approximation and scales as O(N) per time step, with N being with the total number of nodes. To our knowledge, this is the first implementation of the RBF-FD method to leverage GPU accelerators for the solution of PDEs. Additionally, this implementation is the first to span both multiple CPUs and multiple GPUs. OpenCL kernels target the GPUs and inter-processor communication and synchronization is managed by the Message Passing Interface (MPI). We verify our implementation of the RBF-FD method with two hyperbolic PDEs on the sphere, and demonstrate up to 9x speedup on a commodity GPU with unoptimized kernel implementations. On a high performance cluster, the method achieves up to 7x speedup for the maximum problem size of 27,556 nodes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Finite difference numerical method for the superlattice Boltzmann transport equation and case comparison of CPU(C) and GPU(CUDA) implementations

We present a finite difference numerical algorithm for solving two dimensional spatially homogeneous Boltzmann transport equation which describes electron transport in a semiconductor superlattice subject to crossed time dependent electric and constant magnetic fields. The algorithm is implemented both in C language targeted to CPU and in CUDA C language targeted to commodity NVidia GPU. We compare performances and merits of one implementation versus another and discuss various software optimisation techniques.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A review on advances in oxidative coupling of methane (OCM) for industrial use and prospects of CO 2 –H 2 O splitting integration

The discovery of shale gas reserves has encouraged the development of direct methods for methane conversion into valuable chemicals, offering an alternative to indirect approaches that involve an energy-intensive and intermittent syngas production step, leading to high CO 2 emissions. Amongst the direct methods, the oxidative coupling of methane (OCM) is a potential pathway to reduce CO 2 emissions and can produce commodity chemicals such as ethylene, a chemical regarded as central to the petrochemical industry. Even though OCM has been studied for over four decades, the technology still has not found commercial application. Amongst the challenges regarding industrial deployment of OCM, the most significant one is the requirement of a high ethylene yield of 30 % which is currently reported to be around 20 %. Moreover, the highly exothermic nature of the process and controlling the carbon selectivity over oxides of carbon (COx) is the heart of the problem. Numerous researchers have presented promising results in terms of catalysts, reactor designs and feeding strategies for OCM. However, due to lack of inclusiveness in the results, none of the combination of catalysts, reactors and system optimizations has been able to bring about its industrial viability. The current paper presents an extensive review of the noteworthy attempts to achieve industrial targets for OCM. Moreover, a comprehensive criteria is presented which highlights the desired end state for the industrial deployment of OCM technology. Furthermore, the criteria is based on literature survey and a comparison with industrially deployed ethylene production plants i.e., naphtha or ethane steam cracker plants. Finally, a novel integration technology is presented which includes a combination of OCM and CO 2 -H 2 O splitting in a chemical looping reactor design to enable efficient energy utilization and minimal heat losses to the environment.

CO2 Splitting↗
DOE OSTI2024

Electrochemical sulfate production from sulfide-containing wastewaters and integration with electrochemical nitrogen recovery

Electrochemical methods can help manage sulfide in wastewater, which poses environmental and health concerns due to its toxicity, malodor, and corrosiveness. In addition, sulfur could be recovered as fertilizer and commodity chemicals from sulfide-containing wastewaters. Wastewater characteristics vary widely among wastewaters; however, it remains unclear how these characteristics affect electrochemical sulfate production. Here, in this study, we evaluated how four characteristics of influent wastewaters (electrolyte pH, composition, sulfide concentration, and buffer strength) affect sulfide removal (sulfide removal rate, sulfide removal efficiency) and sulfate production metrics (sulfate production rate, sulfate production selectivity). We identified that electrolyte pH (3 × difference, i.e., 25.1 to 84.9 μM h –1 in average removal rate within the studied pH range) and sulfide concentration (16 × difference, i.e., 82.1 to 1347.2 μM h –1 in average removal rate) were the most influential factors for electrochemical sulfide removal. Sulfate production was most sensitive to buffer strength (6 × difference, i.e., 4.4 to 27.4 μM h –1 in average production rate) and insensitive to electrolyte composition. Together, these results provide recommendations for the design of wastewater treatment trains and the feasibility of applying electrochemical methods to varying sulfide-containing wastewaters. In addition, we investigated a simultaneous multi-nutrient (sulfur and nitrogen) process that leverages electrochemical stripping to further enhance the versatility and compatibility of electrochemical nutrient recovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Remote visual analysis of large turbulence databases at multiple scales

The remote analysis and visualization of raw large turbulence datasets is challenging. Current accurate direct numerical simulations (DNS) of turbulent flows generate datasets with billions of points per time-step and several thousand time-steps per simulation. Until recently, the analysis and visualization of such datasets was restricted to scientists with access to large supercomputers. The public Johns Hopkins Turbulence database simplifies access to multi-terabyte turbulence datasets and facilitates the computation of statistics and extraction of features through the use of commodity hardware. In this paper, we present a framework designed around wavelet-based compression for high-speed visualization of large datasets and methods supporting multi-resolution analysis of turbulence. By integrating common technologies, this framework enables remote access to tools available on supercomputers and over 230 terabytes of DNS data over the Web. Finally, the database toolset is expanded by providing access to exploratory data analysis tools, such as wavelet decomposition capabilities and coherent feature extraction.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Who Did the Ethanol Tax Credit Benefit? An Event Analysis of Subsidy Incidence

At the end of 2011, the Volumetric Ethanol Excise Tax Credit (VEETC), which had subsidized the blending of ethanol in gasoline, was allowed to expire. During its tenure, the subsidy was the subject of intense scrutiny concerning who benefited from its existence. Using commodity price data, we estimate the subsidy incidence accruing to corn farmers, ethanol producers, gasoline blenders, and gasoline consumers around the time of expiration. Our empirical approach contributes methodologically to the event studies literature by analyzing futures contract prices (as opposed to spot prices) when possible. Ultimately, we find compelling evidence that, at the date of VEETC expiration, ethanol producers captured about 25 cents of the 45 cents subsidy per gallon of ethanol blended. We find suggestive, albeit inconclusive, evidence that a portion of this benefit (about 5 cents per gallon) was passed further upstream from ethanol producers to corn farmers. Most of the remainder seems most likely to have been captured by the blenders themselves. On the petroleum side, we find no evidence that oil refiners captured any part of the subsidy. We also find no evidence that the subsidy was passed downstream to gasoline consumers in the form of lower gasoline prices.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Identifying common stored product insects using automated deep learning methods

Monitoring stored product insect pests is a common practice for post-harvest management of stored grain and grain-based commodities, which helps ensure product quality from harvest to final consumer. Current methods of sampling and monitoring can be time-consuming, labor-intensive, expensive and require expertise in insect identification. Therefore, this study aims to develop an image-based automated identification system for common stored product insect species using deep-learning methods. Top-down images of the common stored product adult insect species of Rhyzopertha dominica, Cryptolestes ferrugineus, Tribolium castaneum, Sitophilus oryzae, and Oryzaephilus surinamensis were acquired and analyzed. Deep learning-based, state-of-the-art Convolutional Neural Networks (CNN) models (ResNet-50, MobileNet-v2, DarkNet-53, and EfficientNet-b0) were fine-tuned with a transfer learning approach to classify the insect species. All models were able to correctly identify the insect species with at least 96% accuracy and with few misclassifications. One issue with trained CNNs is that they do not explain the reasoning for the classification and are often called a “black box”. Therefore, visualization methods called Gradient-weighted Class Activation Mapping (Grad-CAM) were implemented to explore the black box network. The Grad-CAM uses heat maps to highlight the major image features that the network focused on to make insect species predictions. The Grad-CAM verifies the network's prediction and also helps improve network performance. This study contributes to the overall goal of developing a camera-based system for monitoring stored grain insects. As a result, the developed system would empower warehouse, flour mills, and other food facilities with a tool to quickly and accurately identify insect species in stored product environments and could be implemented as part of a close to real-time monitoring system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

The many phases of CaC{sub 2}

Polymorphic CaC{sub 2} was prepared by reacting mixtures of CaH{sub 2} and graphite with molar ratios between 1:1.8 and 1:2.2 at temperatures between 700 and 1400 °C under dynamic vacuum. These conditions provided a well controlled, homogeneous, chemical environment and afforded products with high purity. The products, which were characterized by powder X-ray diffraction, solid state NMR and Raman spectroscopy, represented mixtures of the three known polymorphs, tetragonal CaC{sub 2}-I and monoclinic CaC{sub 2}-II and -III. Their proportion is dependent on the nominal C/CaH{sub 2} ratio of the reaction mixture and temperature. Reactions with excess carbon produced a mixture virtually free from CaC{sub 2}-I, whereas high temperatures (above 1100 °C) and C-deficiency favored the formation of CaC{sub 2}-I. From first principles calculations it is shown that CaC{sub 2}-I is dynamically unstable within the harmonic approximation. This indicates that existing CaC{sub 2}-I is structurally/dynamically disordered and may possibly even occur as slightly carbon-deficient phase CaC{sub 2-δ}. It is proposed that monoclinic II is the ground state of CaC{sub 2} and polymorph III is stable at temperatures above 200 °C. Tetragonal I represents a metastable, heterogeneous, phase of CaC{sub 2}. It is argued that a complete understanding of the occurrence of three room temperature modifications of CaC{sub 2} will require a detailed characterization of compositional and structural heterogeneities within the high temperature form CaC{sub 2}-IV, which is stable above 450 °C. The effect of high pressure on the stability of the monoclinic forms of CaC{sub 2} was studied in a diamond anvil cell using Raman spectroscopy. CaC{sub 2}-II and -III transform into tetragonal CaC{sub 2}-I at about 4 and 1GPa, respectively. - Graphical abstract: The famous tetragonal form of CaC{sub 2}, CaC{sub 2}-I, is dynamically unstable. Why does it exist? Display Omitted - Highlights: • Critical review of complex polymorphism of the commodity chemical CaC{sub 2}. • Tetragonal CaC{sub 2}-I is identified as dynamical instable and its existence attributed to disorder. • With pressure monoclinic CaC{sub 2}-II and –III transform into tetragonal CaC{sub 2}-I. • The high temperature form CaC{sub 2}-IV is assigned a key role for understanding the polymorphism of CaC{sub 2}.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

High entropy alloys as catalysts: A focused review

A brief literature review of recent experimental and computational efforts on the use of high entropy alloys (HEAs) as catalysts is presented, while also sharing some perspectives and future insights. To fully broach the vast compositional possibilities of HEA materials, integrating computational modeling with high-throughput experimental synthesis and validation is necessary to accelerate their design and development. Once identified, specific HEAs can be a class of materials for the next generation of catalysts when addressing global challenges related to energy independence, commodity chemical production, environmental remediation, abating emissions, and modernized domestic supply chain resilience.

42 - ENGINEERING↗
DOE OSTI2021

Design of a bifunctional TEMPO-tertiary amine mesoporous silica catalyst for the three-step cascade synthesis of a chromene derivative

A key challenge is design of materials and processes whereby competing reagents or conditions do not harm the multi-step sequence, thus allowing for more efficient chemical synthesis with elimination of work-up and separation steps. In this work, a three-step reaction cascade is performed using a porous bifunctional dimethylpropylamine-TEMPO-MCM41 catalyst, converting the commodity chemicals benzyl alcohol, sodium hypochlorite, and malononitrile to a biologically active anti-cancer, and anti-malarial 2-amino-chromene derivative. The cascade first utilizes a TEMPO-catalyzed oxidation of benzyl alcohol to benzaldehyde with NaOCl as the terminal oxidant. This is followed by a two-step, dual base catalyzed Knoevenagel condensation with malononitrile followed by a Michael addition with lawsone. Optimal conditions converting benzyl alcohol to 2-amino-5,10-dioxo-4-phenyl-5,10-dihydro-4H-benzo[g]chromene-3-carbonitrile include the delayed addition of malononitrile and lawsone during the three-step reaction sequence, which results in a 2-amino-chromene yield of over 80%. The importance of stepwise reagent addition is rationalized due to the unfavorable adsorption of acidic lawsone on the surface-grafted base catalyst. Tertiary Brønsted base sites of dimethylpropylamine outperform the more Lewis basic primary propylamine functionalized catalyst. This work outlines a simple and effective method for generating mesoporous materials with two types of active sites via co-condensation and thiol-ene coupling procedures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

A cell-free system for production of 2,3-butanediol is robust to growth-toxic compounds

The need for sustainable, low-cost production of bioenergy and commodity chemicals is increasing. Unfortunately, the engineering potential of whole-cell catalysts to address this need can be hampered by cellular toxicity. When such bottlenecks limit the commercial feasibility of whole-cell fermentation, cell-free, or in vitro, based approaches may offer an alternative. Here, we assess the impact of three classes of growth toxic compounds on crude extract-based, cell-free chemical conversions. As a model system, we test a metabolic pathway for conversion of glucose to 2,3-butanediol (2,3-BDO) in lysates of Escherichia coli . First, we characterized 2,3-BDO production with different classes of antibiotics and found, as expected, that the system is uninhibited by compounds that prevent cell growth by means of cell wall replication and DNA, RNA, and protein synthesis. Second, we considered the impact of polar solvent addition (e.g., methanol, n-butanol). We observed that volumetric productivities (g/L/h) were slowed with increasing hydrophobicity of added alcohols. Finally, we investigated the effects of using pretreated biomass hydrolysate as a feed stock, observing a 25% reduction in 2,3-BDO production as a result of coumaroyl and feruloyl amides. Overall, we find the cell-free system to be robust to working concentrations of antibiotics and other compounds that are toxic to cell growth, but do not denature or inhibit relevant enzymes.

09 BIOMASS FUELS↗
DOE OSTI2021

Ammonia separation from N 2 and H 2 over LTA zeolitic imidazolate framework membranes

LTA type zeolitic imidazolate framework membranes denoted as ZIF-21 were synthesized and evaluated for the separation of a commodity chemical, ammonia, from nitrogen and hydrogen. Membranes were grown using secondary seeded growth. Ammonia permeances were as high as 1727 GPU, with NH 3 /N 2 , and NH 3 /H 2 ideal selectivities of 35, and 12 respectively. ZIF-21 membranes were also evaluated for gas mixtures composed of 13.8:86.2 NH 3 /N 2 and NH 3 /H 2 , with mixture separation selectivities as high as 7.6 for NH 3 /N 2 . Differences in adsorption, and diffusivities were identified as the key separation mechanisms. Specifically, for both gas pairs the polar-polar interaction between ammonia and the linker polar channels, led to the preferential adsorption of ammonia, and therefore favored thermodynamically the separation of ammonia from nitrogen and hydrogen. In addition, for NH 3 /N 2 gas pair, differences in diffusivities was a contributing separation mechanism. For NH 3 /H 2 gas pair, due to the faster hydrogen diffusivity, the kinetic contribution was a strong competing separation mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Flux balance analysis indicates that methane is the lowest cost feedstock for microbial cell factories

The low cost of natural gas has driven significant interest in using C 1 carbon sources (e.g. methane, methanol, CO, syngas) as feedstocks for producing liquid transportation fuels and commodity chemicals. Given the large contribution of sugar and lignocellulosic feedstocks to biorefinery operating costs, natural gas and other C 1 sources may provide an economic advantage. To assess the relative costs of these feedstocks, we performed flux balance analysis on genome-scale metabolic models to calculate the maximum theoretical yields of chemical products from methane, methanol, acetate, and glucose. Yield calculations were performed for every metabolite (as a proxy for desired products) in the genome-scale metabolic models of three organisms: Escherichia coli (bacterium), Saccharomyces cerevisiae (yeast), and Synechococcus sp. PCC 7002 (cyanobacterium). The calculated theoretical yields and current feedstock prices provided inputs to create comparative feedstock cost surfaces. Our analysis shows that, at current market prices, methane feedstock costs are consistently lower than glucose when used as a carbon and energy source for microbial chemical production. Conversely, methanol is costlier than glucose under almost all price scenarios. Acetate feedstock costs could be less than glucose given efficient acetate production from low-cost syngas using nascent biological gas to liquids (BIO-GTL) technologies. Furthermore, our analysis suggests that research should focus on overcoming the technical challenges of methane assimilation and/or yield of acetate via BIO-GTL to take advantage of low-cost natural gas rather than using methanol as a feedstock.

09 BIOMASS FUELS↗
DOE OSTI2022

A review study of rare Earth, Cobalt, Lithium, and Manganese in Coal-based sources and process development for their recovery

The world’s majority predominantly relies on foreign sources for supplying critical minerals. This renders the countries susceptible to supply chain disruption and urges them to develop alternative sources to compete in technological advancements. Among many proven newly identified sources, coal and coal-based materials present their opportunities. Due to the complex structure of coal, many mineral forms can be found in coal-related sources, including critical element-containing minerals. Among the fifty critical elements and minerals defined by the USGS, the rare earth elements, cobalt, lithium, and manganese, are particularly significant as they have enormous importance in high-technology product development. These critical metals can be found in high concentrations in coal-derived sources, such as coal refuse, coal combustion products, and coal acid mine drainage, and be recovered through various separation techniques. Further, this study aims to advance the understanding of these elements' extraction and commercial potential from coal and coal-related sources and help address the world's challenges in the critical mineral supply chain. The concentrations and occurrences of these four commodities in coal-related sources were first reviewed. Later, their recovery processes were discussed, and a conceptual process flowsheet was proposed to selectively recover the rare earth elements, lithium, cobalt, and manganese from coal-based sources.

58 GEOSCIENCES↗
DOE OSTI2016

Using the automata processor for fast pattern recognition in high energy physics experiments. A proof of concept

Here, we explore the Micron Automata Processor (AP) as a suitable commodity technology that can address the growing computational needs of pattern recognition in High Energy Physics (HEP) experiments. A toy detector model is developed for which an electron track confirmation trigger based on the Micron AP serves as a test case. Although primarily meant for high speed text-based searches, we demonstrate a proof of concept for the use of the Micron AP in a HEP trigger application.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

A framework and calculator for evaluating the impacts of shelf life extension and other food loss and waste reduction technologies

Optimization of the food supply chain (FSC) depends on reducing food waste, especially at the consumer stage, where a substantial portion of food is not eaten, but instead disposed of via landfill, incineration, or in-sink disposals. One key strategy is to increase the time that consumers have before food goes bad or expires. This study developed a framework to assess the efficacy of shelf-life extension (SLE) technologies for mitigating food loss and waste (FLW), such as packaging improvements. The impact flows through the entire FSC, reducing FLW, energy use, and other inputs at each stage. The framework and resulting calculator can be used to evaluate the impact of FLW reduction at any stage for any food commodity. As shown by two SLE cases, the calculator is valuable for policy-makers, government entities, and professionals, specifically those in marketing, business development, and capital projects teams, to comprehensively evaluate the impacts of FLW reduction technologies and practices. The framework and calculator are sensitive to the shape of the consumption curve, the fraction of inedible waste, and the current shelf life. The calculator was used to assess the impacts of the United States goal of reducing food waste by consumers through various SLE lengths. It was found that uptake of several near-ready-to-deploy SLE technologies would reduce annual food production demand by about 10–19 MMT and supply chain energy consumption by 240–410 PJ in the United States.

Food loss and waste (FLW)↗