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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Energy savings potential from improved building controls for the US commercial building sector

The U.S. Department of Energy’s (DOE’s) Building Technologies Office (BTO) sponsored a study to determine the potential national savings achievable in the commercial building sector through widespread deployment of best practice controls, elimination of system and component faults, and use of better sensing. Detailed characterization of potential savings was one source of input to set research, development, and deployment (RD&D) goals in the field of building sensors and controls. DOE’s building energy simulation software, EnergyPlus, was employed to estimate the potential savings from 34 measures in 9 building types and across 16 climates representing almost 57% of commercial building sector energy consumption. In addition to estimating savings from individual measures, three packages of measures were created to estimate savings from the packages. These packages represented an 1) efficient building, 2) typical building, and 3) inefficient building. To scale the results from individual measures or a package to the national scale, building weights by building type and climate locations from the Energy Information Administration’s 2012 Commercial Building Energy Consumption Survey (CBECS) were used. The results showed significant potential for energy savings across all building types and climates. The total site potential savings from individual measures by building type and climate location ranged between 0% and 25%. The total site potential savings by building type aggregated across all climates (using the CBECS building weights) for each measure varied between 0% and 16%. The total site potential savings aggregated across all building types and climates for each measure varied between 0% and 11%. Some individual measures had negative savings because correcting underlying operational problems (e.g., inadequate ventilation) resulted in increased energy consumption. When combined into packages, the overall national savings potential is estimated to be 29%; seven of the nine building types were in the range of 23 to 29% and two exceeded 40%. The total potential national site savings in for each building type ranged between 95x106 GJ (0.09 Quadrillion British thermal units [Quads]; Large Hotels) to 222x106 GJ (0.21 Quads; Large Office, Hospital Administrative areas, and College/University), resulting in total site savings of 1,393x106 GJ (1.32 Quads) when the three packages are applied to the U.S. commercial buildings stock. Using the source (or primary) energy conversion factors of 1.05 for natural gas and 3.14 for electricity resulted in an approximate potential primary energy savings of 2,912x106 GJ (2.76 Quads), which would be 15% of the sector’s 2015 use of approximately 18,991x106 GJ (18 Quads). Extrapolating the results for other building types not analyzed as part of this study, the primary energy savings could be in the range of 4,220x106 GJ to 5,275x106 GJ (4 to 5 Quads). If this savings potential is realized, it would be equivalent to not combusting 180 to 230 million tons of coal or reducing the energy impacts, at today’s energy intensities, of the per capita consumption of 12 to 15 million people in the U.S. To realize most of this potential savings, many gaps can be addressed through RD&D, as recommended in this paper.

Fernandez, Nick↗
DOE OSTI2025

A Machine Learning Framework for Predicting Microphysical Properties of Ice Crystals From Cloud Particle Imagery

The microphysical properties of ice crystals are important because they significantly alter the radiative properties and spatiotemporal distributions of clouds, which in turn strongly affect Earth's climate. However, it is challenging to measure key properties of ice crystals, such as mass or morphological features. Here, we present a proof-of-concept framework for predicting three-dimensional (3D) microphysical properties of ice crystals from in situ two-dimensional (2D) imagery. First, we computationally generated synthetic ice crystals using 3D modeling software along with geometric parameters estimated from the 2021 Ice Cryo-Encapsulation Balloon (ICEBall) field campaign. Then, we used synthetic crystals to train machine learning (ML) models to predict effective density ($ρ_e$), effective surface area ($A_e$), and number of bullets ($N_b$) from synthetic rosette imagery. On unseen synthetic images, our ML models accurately predicted ice crystal properties. ResNet-18 performed best, achieving $R^2$ values of 0.99 and 0.98 for $ρ_e$ and $A_e$, respectively, and MAE of 0.10 for mathematical equation in single view tasks. Stereo view ResNet-18 further reduced RMSE by 40% for $ρ_e$ and $A_e$ and reduced MAE by 0.08 for $N_b$. This work provides a novel ML-driven framework for estimating ice microphysical properties from in situ imagery, which will allow for downstream constraints on microphysical parameterizations, such as the mass-size relationship.

Ko, J. [Columbia Univ., New York, NY (United State↗
DOE OSTI2013

Rneshaps

This software is used to combine output files US EPA CAp88-PC software (http://www.epa.gov/radiation/assessment/CAP88/aboutcap88.html) and estimate input parameters for CAP88-PC. Also includes features for tabular and graphical review of results.

MacQueen, D.H.↗
DOE OSTI2016

Moving Toward an Optimal and Automated Geospatial Network for CCUS Infrastructure

Modifications in the global climate are being driven by the anthropogenic release of greenhouse gases (GHG) including carbon dioxide (CO 2 ) (Middleton et al. 2014). CO 2 emissions have, for example, been directly linked to an increase in total global temperature (Seneviratne et al. 2016). Strategies that limit CO 2 emissions—like CO 2 capture, utilization, and storage (CCUS) technology—can greatly reduce emissions by capturing CO 2 before it is released to the atmosphere. However, to date CCUS technology has not been developed at a large commercial scale despite several promising high profile demonstration projects (Middleton et al. 2015). Current CCUS research has often focused on capturing CO 2 emissions from coal-fired power plants, but recent research at Los Alamos National Laboratory (LANL) suggests focusing CCUS CO 2 capture research upon industrial sources might better encourage CCUS deployment. To further promote industrial CCUS deployment, this project builds off current LANL research by continuing the development of a software tool called SimCCS, which estimates a regional system of transport to inject CO 2 into sedimentary basins. The goal of SimCCS, which was first developed by Middleton and Bielicki (2009), is to output an automated and optimal geospatial industrial CCUS pipeline that accounts for industrial source and sink locations by estimating a Delaunay triangle network which also minimizes topographic and social costs (Middleton and Bielicki 2009). Current development of SimCCS is focused on creating a new version that accounts for spatial arrangements that were not available in the previous version. This project specifically addresses the issue of non-unique Delaunay triangles by adding additional triangles to the network, which can affect how the CCUS network is calculated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Fast BLT Code

This note discusses numerical algorithmic software design considerations and performance estimates for a fast BLT coupling code [1] written in c++. The aim of this code is to conduct faster parameter studies over line orientations. The original matlab code was written by Mike Rivera. Art Barnes ported this code to julia. I rewrote portions of the code for speed improvement, mainly to eliminate some redundant computation when calculating many line orientations. But this code is still far from optimal.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Analysis of ISOCS Measurements to Establish Methodology Uncertainty

Qualification measurements were performed at the US Department of Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL) on a variety of measurement standards. These measurements will be used to qualify the In-Situ Object Counting System (ISOCS) measurement method with a high-purity germanium (HPGe) detector for use at ORNL. Measured items include uranium isotopic standards, filter papers coated with uranium oxide (U 3 O 8 ), U 3 O 8 line sources, and a uranium tetrafluoride (UF 4 ) source. The 235 U mass was estimated using the ISOCS calibration software for each source and compared with the declared isotope mass value.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Analysis and Recommendation of Tritium Gas Continuous Air Monitor Alarm Setpoints for the RPL Stack Exhaust

The Radiochemical Processing Laboratory (RPL) tritium continuous air monitor (CAM) is used for near real-time detection of tritium gas (i.e., elemental tritium [HT] and tritiated water vapor [HTO]) in the stack exhaust. The CAM interfaces with software developed by the Pacific Northwest National Laboratory (PNNL)—called the “PNNL OS3700 Tritium Monitoring Software”—that provides near real-time estimates of tritium gas air concentrations and integrated daily activities that are calculated from measured CAM counts. The OS3700 software implements alarm setpoints to alert the facility of larger tritium gas releases that if allowed to persist, could begin to challenge permitted emission and established dose constraints. This report performs a detailed review of historical and current tritium alarm setpoints used at RPL, including discussion of the technical basis used in their development, analysis of alarm frequencies using measured historical data, and performs a detailed dose assessment using more realistic release scenarios and meteorology. Based on the results, the tritium air concentration and integrated daily tritium activity alarm setpoints will remain 2.0 × 10 -5 µCi/ml and 25 Ci/day, respectively. These setpoints achieve the right operational balance in identifying larger releases from planned tritium work at RPL, without being overly conservative so as to cause nuisance alarming. Furthermore, implied doses associated with these setpoints are well below defined and regulatory limits.

325RPL↗
DOE OSTI2020

Quality Assurance Plan for Federal Guidance Report 16

Federal Guidance Report No. 16 will provide risk coefficients for use in projecting the probability of cancer morbidity or mortality from exposure to environmental radionuclides. The derivation of nuclide-specific risk coefficients involves multiple steps, with each step relying on the accuracy of the previous step as well as the numerical data utilized within each step. Thus, to ensure the quality of the derived risk coefficients, it is necessary to evaluate and confirm the quality and proper implementation of input data at each step of the derivation. The Oak Ridge National Laboratory (ORNL) dosimetry research team currently has two largely independent software codes for deriving radiation dose estimates, dose coefficients, and cancer risk coefficients for internally deposited radionuclides: DCAL and QCAL. The agreement of derived values based on alternate codes is an important step in quality assurance (QA) of the risk coefficients produced in this project. DCAL is an integration of the dosimetric software and numerical databases developed at ORNL over the past 25 years for the EPA’s Office of Radiation and Indoor Air (ORIA). QCAL was developed in 2015 to serve as a substitute for DCAL while DCAL was undergoing revision and to provide QA for the updated version of DCAL. The complex methodology employed in the derivation of cancer risk coefficients presents a challenge for QA, and as such, this report describes the QA steps used by the ORNL dosimetry team in this process as implemented in DCAL and QCAL for Federal Guidance Report No. 16.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

SITCOMTN-154: Initial studies of photometric redshifts with LSSTComCam from DP1

This technote holds reports based on the first analyses of the Data Preview 1 (DP1) data by the Science Unit for photometric redshifts. Although photometric redshifts are not an official DP1 data product, the "Photo-z Science Unit" generated photo-z estimates for every galaxy in DP1 using the available multi-band imaging on a best-effort basis. This work included developing training and test datasets by matching DP1 data to high-quality reference redshifts obtained with spectroscopy, Grism data, and multi-band photometry. The Science Unit used the RAIL software package to make photometric redshift estimates using eight different algorithms, developed simple scientific performance metrics, used those metrics to explore how the performance of the algorithms varied with configuration changes, derived more optimized configurations of the algorithms and tested the performance of those configurations. This work, the resulting data products and expected data distribution mechanism are all described there.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

FRAM v5.2 estimation of plutonium and uranium isotopics using digitized 3-D position-sensitive CdZnTe detectors

Gamma-ray spectroscopy is an important tool used in international safeguards to measure plutonium and uranium isotopics. Recently developed, digital, 3-D position-sensitive CdZnTe gamma-ray spectrometers are promising for safeguards, offering improved performance over commonly available CdZnTe systems, with energy resolutions approaching that of high-purity germanium. CdZnTe gamma-ray spectra from plutonium and uranium samples were processed using the commercially available software FRAM v5.2, a tool that estimates plutonium and uranium isotopics from high-purity germanium spectra, across a wide range of materials. Furthermore using digital CdZnTe systems 239 Pu/ 240 Pu isotopic composition and effective 240 Pu percentage are evaluated to within less than 3 sigma statistical measurement uncertainty across reactor to weapons-grade samples, while low and highly-enriched uranium are easily distinguished.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Recent improvements to software used for optimization of SRF linacs

This work describes a software tool that allows one to vary parameters and understand the effects on the optimized costs of construction plus 10 year operations of an SRF linac, where operation costs includes the cost of the electrical utilities but not the labor or other costs. The program includes estimates for the associated cryogenic facility, and controls hardware. The software interface provides the ability to vary the cost of the different aspects of the machine as well as to change the cryomodule and cavity types. Additionally, this work will describe the recent improvements to the software that allow one to estimate the costs of energy-recovery based linacs and to enter arbitrary values of the low field Q0 and Q0 slope. The initial goal when developing the software was to convert a spreadsheet format to a graphical interface and to allow the ability to sweep different parameter sets. The tools also allow one to compare the cost of the different facets of the machine design and operations so as to better understand tradeoffs. An example of how it was used to independently investigate cost optimization tradeoffs for the LCLS-II linac will also be presented.

Powers, Tom J.↗
DOE OSTI2013

Hiereachical Bayesian Model for Combining Geochemical and Geophysical Data for Environmental Applications Software

Development of a hierarchical Bayesian model to estimate the spatiotemporal distribution of aqueous geochemical parameters associated with in-situ bioremediation using surface spectral induced polarization (SIP) data and borehole geochemical measurements collected during a bioremediation experiment at a uranium-contaminated site near Rifle, Colorado. The SIP data are first inverted for Cole-Cole parameters including chargeability, time constant, resistivity at the DC frequency and dependence factor, at each pixel of two-dimensional grids using a previously developed stochastic method. Correlations between the inverted Cole-Cole parameters and the wellbore-based groundwater chemistry measurements indicative of key metabolic processes within the aquifer (e.g. ferrous iron, sulfate, uranium) were established and used as a basis for petrophysical model development. The developed Bayesian model consists of three levels of statistical sub-models: 1) data model, providing links between geochemical and geophysical attributes, 2) process model, describing the spatial and temporal variability of geochemical properties in the subsurface system, and 3) parameter model, describing prior distributions of various parameters and initial conditions. The unknown parameters are estimated using Markov chain Monte Carlo methods. By combining the temporally distributed geochemical data with the spatially distributed geophysical data, we obtain the spatio-temporal distribution of ferrous iron, sulfate and sulfide, and their associated uncertainity information. The obtained results can be used to assess the efficacy of the bioremediation treatment over space and time and to constrain reactive transport models.

Chen, Jinsong↗
DOE OSTI2022

Energy-Storing Cryogenic Carbon Capture™ for Utility and Industrial-scale Processes (Final Report)

This project leverages work completed under funding from previous U.S. Department of Energy (DOE) projects and other sources of funding around the Cryogenic Carbon Capture Process™ (CCC). The purpose of this project is to further develop a perturbation of the CCC process that stores energy called the Cryogenic Carbon Capture™ Energy Storing (CCC-ES) process. The successful completion of the tasks in this project has prepared the CCC-ES process for scaling and developed initial plans and a feasibility analysis for an engineering-scale or small-commercial scale system that can store at least 10 MWh of energy. The specific areas of work in this project are: (1) Develop a conceptual, site-specific integrated process flow diagram: Sustainable Energy Solutions (SES) developed a conceptual, site-specific plan including a process flow diagram for integrating CCC-ES at a specific location. The proposed system was based on a typical engineering-scale CCC system designed to capture 30-50 metric tonnes of CO 2 per day (TPD), with modifications and additional changes and equipment put in place to add the energy storage element to the system. The 30-50 TPD scale corresponds to the required 10 MWh of stored energy. This task includes updating simulation software for transient analysis. SES also coordinated with the Jim Bridger Power Plant in Point of Rocks, Wyoming to get site-specific data. Using these data, SES completed site-specific preliminary process flow diagrams, estimated capital and operating costs for the CCC-ES system, and used the upgraded software package to estimate the primary figures of merit. (2) Complete a technoeconomic analysis (TEA): SES completed a full-scale TEA of the CCC-ES system to meet specific success criteria. This TEA used process information from the host site selected above. (3) Technology and data gap assessment for the CCC-ES process: As part of the technology gap assessment, SES performed an assessment of the best alternative energy storage solutions including figures of merit and operational strengths and weaknesses. SES then compared the proposed system with a discussion of how it addresses the weaknesses of alternative systems, showing for example a cost of stored energy at less than $50/MWh and with a roundtrip efficiency of greater than 95%. This assessment includes technical and other risk analyses and technology gaps with research and development needs to commercialize the process by 2030. Finally, work includes a commercialization roadmap/development pathway outlining the major milestones to move to a commercially operating CCC-ES system. (4) Phase II pre-FEED project plan: SES completed a project plan for the Phase II pre-FEED analysis using the same host site as in the Phase I conceptual study.

03 NATURAL GAS↗
DOE OSTI2018

A Projected Estimate of the Reionization Optical Depth Using the CLASS Experiment’s Sample Variance Limited E-mode Measurement

Here, we analyze simulated maps of the Cosmology Large Angular Scale Surveyor (CLASS) experiment and recover a nearly cosmic variance limited estimate of the reionization optical depth τ. We use a power spectrum-based likelihood to simultaneously clean foregrounds and estimate cosmological parameters in multipole space. Using software specifically designed to constrain τ, the amplitude of scalar fluctuations A s , and the tensor-to-scalar ratio r, we demonstrate that the CLASS experiment will be able to estimate τ within a factor of two of the cosmic variance limit allowed by full-sky cosmic microwave background polarization measurements. Additionally, we discuss the role of CLASS's τ constraint in conjunction with gravitational lensing of the CMB on obtaining a ≳4σ measurement of the sum of the neutrino masses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A workflow for automatic generation and efficient refinement of individual pressure-dependent networks

Manual chemical kinetic model construction often requires modelists to at least implicitly guess all possible decay pathways and their relative fluxes for all important species. We present a workflow and associated tool for automatic generation and re finement of pressure-dependent networks that should enable modelists to efficiently and comprehensively identify decay pathways and estimate respective parameters for chemical species. This tool combines the capabilities of the Reaction Mechanism Generator (RMG) software to generate possible reaction paths, determine thermochemistry, approximate rate coefficients and estimate frequencies with the capabilities of the Arkane software to use quantum chemical parameters to compute thermochemistry and pressure dependent rates. A flux-based algorithm is used to decide which isomers to add to the network. Isomers added to the network are reacted to form other channels. When enough of the flux is accounted for by the isomers and bimolecular product channels, the generation process terminates to yield a comprehensive network. Network sensitivity analysis is applied to the network to identify the most important wells and barriers that can be refined using quantum chemistry calculations. Iterative refinement can then be used to achieve accuracy. The comprehensive network can be easily reduced using energy and flux-based algorithms to the most important channels and isomers in the network.

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

Wire Arc Additive Manufacturing

Project highlight. This project designs and implements a new additive manufacturing capability at Savannah River National Laboratory. Wire Arc Additive Manufacturing is an Advanced Manufacturing technology that enables materials and energy savings by producing materials that are in near net shapes to minimize material losses compared to conventional forging and machining techniques. Wire arc additive manufacturing is an evolving technology that can be used to fabricate large components with significantly less materials waste than conventional processing. This project includes an engineering model, an aspect that is largely overlooked in the Additive Manufacturing modeling work where the emphasis has been on mechanistic and microscopic modeling, to estimate the residual stresses and distortions. The Abaqus Weld Interface software coupled with user subroutines in Fortran enable the local cooling rates to be estimated to provide a coarse scale model for the secondary dendrite arm spacing, a parameter useful to estimate mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Reducing Contingency through Sampling at the Luckey FUSRAP Site - 13186

Typically, the greatest risk in developing accurate cost estimates for the remediation of hazardous, toxic, and radioactive waste sites is the uncertainty in the estimated volume of contaminated media requiring remediation. Efforts to address this risk in the remediation cost estimate can result in large cost contingencies that are often considered unacceptable when budgeting for site cleanups. Such was the case for the Luckey Formerly Utilized Sites Remedial Action Program (FUSRAP) site near Luckey, Ohio, which had significant uncertainty surrounding the estimated volume of site soils contaminated with radium, uranium, thorium, beryllium, and lead. Funding provided by the American Recovery and Reinvestment Act (ARRA) allowed the U.S. Army Corps of Engineers (USACE) to conduct additional environmental sampling and analysis at the Luckey Site between November 2009 and April 2010, with the objective to further delineate the horizontal and vertical extent of contaminated soils in order to reduce the uncertainty in the soil volume estimate. Investigative work included radiological, geophysical, and topographic field surveys, subsurface borings, and soil sampling. Results from the investigative sampling were used in conjunction with Argonne National Laboratory's Bayesian Approaches for Adaptive Spatial Sampling (BAASS) software to update the contaminated soil volume estimate for the site. This updated volume estimate was then used to update the project cost-to-complete estimate using the USACE Cost and Schedule Risk Analysis process, which develops cost contingencies based on project risks. An investment of $1.1 M of ARRA funds for additional investigative work resulted in a reduction of 135,000 in-situ cubic meters (177,000 in-situ cubic yards) in the estimated base volume estimate. This refinement of the estimated soil volume resulted in a $64.3 M reduction in the estimated project cost-to-complete, through a reduction in the uncertainty in the contaminated soil volume estimate and the associated contingency costs. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

PyPWA: A Partial-Wave/Amplitude Analysis Software Framework

The PyPWA project aims to develop a software framework for Partial Wave and Amplitude Analysis of data; providing the user with software tools to identify resonances from multi-particle final states in photoproduction. Most of the code is written in Python. The software is divided into two main branches: one general-shell where amplitude's parameters (or any parametric model) are to be estimated from the data. This branch also includes software to produce simulated data-sets using the fitted amplitudes. A second branch contains a specific realization of the isobar model (with room to include Deck-type and other isobar model extensions) to perform PWA with an interface into the computer resources at Jefferson Lab. We are currently implementing parallelism and vectorization using the Intel's Xeon Phi family of coprocessors.

Salgado, Carlos↗