Search NASA⌕ Search

SEARCH · Search NASA

Results for “analysis process”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4

Impact of Active Climate Control Seats on Energy Use, Fuel Use, and CO2 Emissions

A project was developed through collaboration between Gentherm and NREL to determine the impact of climate control seats for light-duty vehicles in the United States. The project used a combination of experimentation and analysis, with experimental results providing critical input to the analysis process. First, outdoor stationary vehicle testing was performed at NREL's facility in Golden, CO using multiple occupants. Two pre-production Ford Focus electric vehicles were used for testing; one containing a standard inactive seat and the second vehicle containing a Gentherm climate control seat. Multiple maximum cool-down and steady-state cooling tests were performed in late summer conditions. The two vehicles were used to determine the increase in cabin temperature when using the climate control seat in comparison to the baseline vehicle cabin temperature with a standard seat at the equivalent occupant whole-body sensation. The experiments estimated that on average, the climate control seats allowed for a 2.61 degrees Celsius increase in vehicle cabin temperature at equivalent occupant body sensation compared to the baseline vehicle. The increased cabin air temperature along with their measured energy usage were then used as inputs to the national analysis process. The national analysis process was constructed from full vehicle cabin, HVAC, and propulsion models previously developed by NREL. In addition, three representative vehicle platforms, vehicle usage patterns, and vehicle registration weighted environmental data were integrated into the analysis process. Both the baseline vehicle and the vehicle with climate control seats were simulated, using the experimentally determined cabin temperature offset of 2.61degrees Celsius and added seat energy as inputs to the climate control seat vehicle model. The U.S. composite annual fuel use savings for the climate control seats over the baseline A/C system was determined to be 5.1 gallons of gasoline per year per vehicle, corresponding to 4.0 grams of CO2/mile savings. Finally, the potential impact of 100 percent adoption of climate control seats on U.S. light-duty fleet A/C fuel use was calculated to be 1.3 billion gallons of gasoline annually with a corresponding CO2 emissions reduction of 12.7 million tons. Direct comparison of the impact of the CCS to the ventilated seat off-cycle credit was not possible because the NREL analysis calculated a combined car/truck savings and the baseline A/C CO2 emissions were higher than EPA. To enable comparison, the CCS national A/C CO2 emissions were split into car/truck components and the ventilated seat credit was scaled up. The split CO2 emissions savings due to the CCS were 3.5 g/mi for a car and 4.4 g/mi for a truck. The CCS saved an additional 2.0 g/mi and 2.5 g/mi over the adjusted ventilated seat credit for a car and truck, respectively.

30 DIRECT ENERGY CONVERSION↗

A Processing and Analytics System for Microscopy Data Workflows: The Pycroscopy Ecosystem of Packages

Major advancements in fields as diverse as biology and quantum computing have relied on a multitude of microscopy techniques. Despite the considerable proliferation of these instruments, significant bottlenecks remain in terms of processing, analysis, storage, and retrieval of the acquired datasets. Aside from lack of file standards, individual domain-specific analysis packages are often disjoint from the underlying datasets, and thus keeping track of analysis and processing steps remains tedious for the end-user, hampering reproducibility. Here, in this study, the pycroscopy ecosystem of packages is introduced, an open-source python-based ecosystem underpinned by a common data model. The data model, termed the N-dimensional spectral imaging data format, is realized in pycroscopy's sidpy package. This package is built on top of dask arrays, thus leveraging dask array attributes, but expanding them to accelerate microscopy relevant analysis and visualization. Several examples of the use of the pycroscopy ecosystem to create workflows for data ingestion and analysis of scanning transmission electron microscopy (STEM) and scanning probe microscopy data are shown. Adoption of such standardized routines will be critical to usher in the next generation of autonomous instruments where processing, computation, and meta-data storage will be critical to overall experimental operations.

97 MATHEMATICS AND COMPUTING↗

Evaluation of the Benefits of ATF, FLEX, and Passive Cooling System for an Enhanced Resilient PWR Model

This report, along with report INL/EXT-19-53556, documents the activities performed by Idaho National Laboratory (INL) during the fiscal year (FY) 2019 for the DOE Light Water Reactor Sustainability (LWRS) Program, Risk-Informed System Analysis (RISA) Pathway, Enhanced Resilient Plant (ERP) Systems research. This report includes additional accident scenarios for risk-informed ATF analysis, and examines the risk impacts of FLEX and passive cooling system on nuclear power plants (NPPs) from additional perspectives. The same analysis process, risk analysis approaches, and analysis tools as in FY 2018 were used for near-term ATF cladding (i.e., Iron-Chromium-Aluminum [FeCrAl] cladding and Chromium [Cr]-coated cladding) designs under the small break loss-of-coolant accident (SBLOCA) scenarios, two types of general transient scenarios (locked rotor and turbine trip), and main steam line break (MSLB) scenarios. Benchmark calculations for ATF analysis using RELAP5-3D and MELCOR are also presented. In addition, based on the generic probabilistic risk assessment (PRA) model, the risk impacts of FLEX and the dynamic natural convection (DNC) system on NPPs are evaluated through a risk-informed decision-making process, i.e., significance determination process (SDP).

99 GENERAL AND MISCELLANEOUS↗

Implementation and Initial Testing of Advanced Processing and Analysis Algorithms for Correlated Neutron Counting

In order to improve the accuracy and capabilities of neutron multiplicity counting, additional quantifiable information is needed in order to address the assumptions that are present in the point model. Extracting and utilizing higher order moments (Quads and Pents) from the neutron pulse train represents the most direct way of extracting additional information from the measurement data to allow for an improved determination of the physical properties of the item of interest. The extraction of higher order moments from a neutron pulse train required the development of advanced dead time correction algorithms which could correct for dead time effects in all of the measurement moments in a self-consistent manner. In addition, advanced analysis algorithms have been developed to address specific assumptions that are made within the current analysis model, namely that all neutrons are created at a single point within the item of interest, and that all neutrons that are produced within an item are created with the same energy distribution. This report will discuss the current status of implementation and initial testing of the advanced dead time correction and analysis algorithms that have been developed in an attempt to utilize higher order moments to improve the capabilities of correlated neutron measurement techniques.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Risk-Informed Analysis for an Enhanced Resilient PWR with ATF, FLEX, and Passive Cooling

This report documents the activities performed by Idaho National Laboratory (INL) during the fiscal year (FY) 2019 for the DOE Light Water Reactor Sustainability (LWRS) Program, Risk-Informed System Analysis (RISA) Pathway, Enhanced Resilient Plant (ERP) Systems research. The purpose of the RISA Pathway research and development is to support plant owner-operator decisions with the aim to improve the economics, reliability, and maintain the high levels of safety of current nuclear power plants over periods of extended plant operations. The concept of ERP refers to the combinations of Accident Tolerant Fuel (ATF), optimal use of Diverse and Flexible Coping Strategy (FLEX), enhancements to plant components and systems, and the incorporation of augmented or new passive cooling systems, as well as improved fuel cycle efficiency. The objective of the ERP research effort is to use the RISA methods and toolkit in industry applications, including methods development and early demonstration of technologies, in order to enhance existing reactors safety features (both active and passive) and to substantially reduce operating costs through risk-informed approaches to plant design modifications to the plant and their characterization. The FY 2019 efforts documented in this report is an extension of those conducted in FY 2018. The same analysis process, risk analysis approaches, and analysis tools as in FY 2018 are used for near-term ATF cladding [i.e., Iron-Chromium-Aluminum (FeCrAl) cladding and Chromium (Cr) coated cladding] designs under the postulated loss of feedwater (LOFW) and steam generator tube rupture (SGTR) accident scenarios. In addition, FLEX analysis was presented for an overview of FLEX equipment and strategies implemented in nuclear industry after Fukushima accident. A FLEX model was developed and incorporated into the generic SAPHIRE model to assess the risk impact from FLEX. FLEX HRA analysis was performed which suggested an approach to HRA with FLEX strategies. Passive cooling system analysis includes an overview of the DNC system, the RELAP5-3D simulations of the DNC system in selected SBO scenarios, and the evaluation of the DNC system risk impact using the generic PRA model.

99 GENERAL AND MISCELLANEOUS↗

Risk-Informed ATF and FLEX Analysis for an Enhanced Resilient BWR Under Design-Basis and Beyond-Design-Basis Accidents

This report documents the activities performed by the Idaho National Laboratory (INL) during fiscal year (FY) 2020 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk-Informed System Analysis (RISA) Pathway, Enhanced Resilient Plant (ERP) Systems research. The purpose of the RISA Pathway research and development is to support plant owner-operator decisions with the aim to improve the economics, reliability, and maintain the high levels of safety of current nuclear power plants over periods of extended plant operations. The concept of ERP refers to the combinations of accident-tolerant fuel (ATF), optimal use of diverse and flexible coping strategy (FLEX), enhancements to plant components and systems, and the incorporation of augmented or new passive cooling systems, as well as improved fuel cycle efficiency. The objective of the ERP research effort is to use the RISA methods and toolkit in industry applications, including methods development and early demonstration of technologies, in order to enhance existing reactors’ safety features (both active and passive) and to substantially reduce operating costs through risk-informed approaches to plant design modifications to the plant and their characterization. One main focus of the FY 2020 efforts documented in this report was to extend the analyses conducted in FYs 2018 and 2019 for a pressurized water reactor (PWR) to a boiling water reactor (BWR). The same analysis process, risk analysis approaches, and analysis tools as in the previous work for PWR were used for a generic BWR with near-term ATF cladding (i.e., Iron-Chromium-Aluminum [FeCrAl] cladding and Chromium [Cr]-coated cladding) designs under the postulated station blackout (SBO) and medium loss-of-coolant (MLOCA) accident scenarios. In addition, a FLEX model was developed and incorporated into a generic BWR probabilistic risk assessment (PRA) model using the INL-developed software tool, Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE), to assess the risk impact from FLEX. The other main focus of the FY 2020 efforts was to advance analysis methods, including developing dynamic approach for FLEX human reliability analysis (HRA) using the INL-developed software tool, Event Modeling Risk Assessment using Linked Diagrams (EMRALD), as well as developing a multicriterion benefit evaluation (MCBE) method for evaluating costs and benefits of safety enhancements in nuclear power plants (NPPs). As a case study, the MCBE method was applied to evaluate the costs and benefits brought by FLEX implementation.

99 GENERAL AND MISCELLANEOUS↗

APPLICATION OF INDUCTIVELY COUPLED PLASMA MASS SPECTROMETRY IN THE ANALYSIS OF PLUTONIUM CONTENT OF FAST CRITICAL ASSEMBLY FUEL DISPOSITION

Outline • Fast Critical Assembly (FCA) Plutonium Fuel Disposition • Brief campaign overview • Savannah River National Laboratory • Analytical capabilities and instrumentation • Typical FCA sample analysis process • Plutonium analysis by quadrupole-inductively coupled plasma-mass spectrometry (Q-ICP-MS) • Method description/development • Instrumentation • Data/control charts

Bonilla, Henry J. [Savannah River National Laborat↗

Geometric Analysis Based Double Closed-loop Iterative Learning Control of Output PDF Shaping of Fiber Length Distribution in Refining Process

In order to improve the pulp quality and to reduce the energy consumption, the fiber length distribution (FLD) is generally employed as one of the important technological indexes in the refining process. Considering that the traditional mean and variance of fiber length are unable to adequately characterize the non-Gaussian distribution properties, this paper proposes a novel geometric analysis based double closed-loop iterative learning control (ILC) method for probability density function (PDF) shaping of output FLD in the refining process. Primarily, a RBF neural network (NN) with Gaussian-type is utilized to approximate the square root PDF in the inner loop, where the RBF basis function parameters (center and width) are tuned between any two adjacent batches by using an ILC law, and the subspace identification method can be applied to establish the state-space model of weight vector. Then, for the sake of accelerating the convergence rate of the closed-loop sysyem, a geometric analysis based ILC method is adopted in the outer loop. Lastly, both simulation and experiments demonstrate the effectiveness and practicability of the proposed approach.

42 ENGINEERING↗

Adaptive Sequential Monte Carlo for Multiple Changepoint Analysis

Process monitoring and control requires detection of structural changes in a data stream in real time. This paper introduces an efficient sequential Monte Carlo algorithm designed for learning unknown changepoints in continuous time. The method is intuitively simple: new changepoints for the latest window of data are proposed by conditioning only on data observed since the most recent estimated changepoint, as these observations carry most of the information about the current state of the process. The proposed method shows improved performance over the current state of the art. Another advantage of the proposed algorithm is that it can be made adaptive, varying the number of particles according to the apparent local complexity of the target changepoint probability distribution. This saves valuable computing time when changes in the changepoint distribution are negligible, and enables re-balancing of the importance weights of existing particles when a significant change in the target distribution is encountered. The plain and adaptive versions of the method are illustrated using the canonical continuous time changepoint problem of inferring the intensity of an inhomogeneous Poisson process, although the method is generally applicable to any changepoint problem. Performance is demonstrated using both conjugate and non-conjugate Bayesian models for the intensity. Lastly, appendices to the article are available online, illustrating the method on other models and applications.

97 MATHEMATICS AND COMPUTING↗

3-Hydroxypropionic acid recovery from fermentation broth through novel downstream processing: Technoeconomic analysis

This study develops and validates a simplified, fully solvent-free downstream processing (DSP) strategy for high-purity recovery of 3-hydroxypropionic acid (3-HP) from real fermentation broth containing 62.3 g/L of 3-HP. Optimized activated carbon treatment achieved 98% color removal, while Amberlite IRA-67 was operated at pH 4.5 and 30 °C to minimize product loss. This is the first integrated demonstration of a fully solvent-free DSP enabling recovery of bio-based 3-HP as both a solid sodium salt and a concentrated aqueous solution, supported by techno-economic analysis. At lab scale, the process achieved 77.3% recovery of sodium 3-HP with 83.2% (w/w) purity and produced a 30% (w/v) aqueous solution. Techno-economic analysis yielded minimum selling prices of $0.551/kg for the solution and $0.892/kg for the salt, both below target thresholds for cost-competitive bio-acrylic acid production. Overall, these results demonstrate an efficient, scalable, and economically viable industrial pathway for 3-HP recovery.

09 BIOMASS FUELS↗

Process Feasibility Analysis of Waste Biomass Valorization to Biochar and Bio-Oil via Slow and Fast Pyrolysis

The United States has abundant biomass and waste feedstock to support the nation's energy addition and affordability targets. Pyrolysis, a thermochemical conversion process, decomposes lignocellulosic feedstocks into liquid, solid, and gaseous fuels that can contribute to the domestic production of biofuels, biopower, and bioproducts. Growing private sector interest in this technology is a key motivation for this comprehensive techno-economic process modeling analysis of a respective biorefinery that includes feedstock preprocessing, slow and fast pyrolysis, and product separation to bio-oil, biochar, and syngas hydrocarbons. Results show that biochar from slow pyrolysis could achieve minimum selling prices (MSPs) of $\$$188-$\$$260/t, competitive with reported market values, while bio-oil from fast pyrolysis is estimated to yield MSPs of $\$$6.49-$\$$9.68/GGE, approximately twice conventional fuel benchmarks. Sensitivity analysis identifies feedstock cost, product yield, and scale as primary cost drivers, while scenarios involving biochar carbon credits and high value applications may substantially improve economics. Overall, these results suggest that continued innovation in feedstock logistics, process integration, and market development will be critical to achieving economically viable and scalable bioproducts.

09 BIOMASS FUELS↗

An expert-systems approach to automatically determining flaw depth within Candu pressure tubes - 221

Delayed Hydride Cracking (DHC) is a crack growth mechanism that occurs in zirconium alloys, including the pressure tubes of CANDU reactors. DHC is caused by hydrogen in solution in zirconium components being diffused to any flaws present, resulting in an increased concentration of hydrogen within these flaws. An increased hydrogen concentration can lead to brittleness, followed by cracking, in high-stress regions of a pressure tube. Regular in-service ultrasonic inspection of CANDU pressure tubes aims to locate and classify any flaws that pose a potential for DHC initiation. A common approach to inspection is the use of a bespoke tool containing multiple ultrasonic transducers to ensure that each point on the pressure tube is inspected from a minimum of three angles during a scan. All flaws from within the inspected pressure tubes must be characterized prior to restarting the reactor, thus the time-consuming analysis process lies on the critical outage path. This process is manually intensive and often requires a significant amount of expert knowledge. A modular system to automatically process outage data to provide decision support to analysts has been developed. This system saves time on the critical outage path while providing repeatable and explicable measurements. Part of the analysis process requires the depth of all flaws to be measured, which is often the most time consuming stage of the analysis process. This paper describes an approach that utilizes captured analysts knowledge to perform automatic flaw depth estimation. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

HyperKube: A Kubernetes Based System for the Automation of Processing and Analysis of Hyperspectral Data Obtained from Multiple Hyperspectral Imaging Systems

Hyperspectral imagery is an emerging field of technology that has enormous potential for remote and proximal sensing in numerous areas of research. The plant phenotyping community is applying this technology to advance the throughput and accuracy of plant phenotypes based on airborne and lab-based hyperspectral imaging technology. Here we report an automated processing and analysis pipeline for four different hyperspectral imaging platforms, discuss the data issues involved, and present a strategy for computing and data architecture to handle hyperspectral data.

47 OTHER INSTRUMENTATION↗

ACTINIDE REMOVAL PROCESS SAMPLE ANALYSIS, CHEMICAL MODELING, AND FILTRATION EVALUATION

Filtration within the Actinide Removal Process (ARP) currently limits the throughput in interim salt processing at the Savannah River Site. In this process, batches of salt solution with Monosodium Titanate (MST) sorbent are concentrated by crossflow filtration. The filtrate is subsequently processed to remove cesium in the Modular Caustic Side Solvent Extraction Unit (MCU) followed by disposal in saltstone grout. The concentrated MST slurry is washed and sent to the Defense Waste Processing Facility (DWPF) for vitrification. During recent ARP processing, there has been a degradation of filter performance manifested as the inability to maintain high filtrate flux throughout a multi-batch cycle. The objectives of this effort were to characterize the feed streams, to determine if solids (in addition to MST) are precipitating and causing the degraded performance of the filters, and to assess the particle size and rheological data to address potential filtration impacts. Equilibrium modelling with OLI Analyzer{sup TM} and OLI ESP{sup TM} was performed to determine chemical components at risk of precipitation and to simulate the ARP process. The performance of ARP filtration was evaluated to review potential causes of the observed filter behavior. Task activities for this study included extensive physical and chemical analysis of samples from the Late Wash Pump Tank (LWPT) and the Late Wash Hold Tank (LWHT) within ARP as well as samples of the tank farm feed from Tank 49H. The samples from the LWPT and LWHT were obtained from several stages of processing of Salt Batch 6D, Cycle 6, Batch 16.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Analysis of TID process, geometry, and bias condition dependence in 14-nm FinFETs and implications for RF and SRAM performance

Here, total ionizing dose results are provided, showing the effects of different threshold adjust implant processes and irradiation bias conditions of 14-nm FinFETs. Minimal radiation-induced threshold voltage shift across a variety of transistor types is observed. Off-state leakage current of nMOSFET transistors exhibits a strong gate bias dependence, indicating electrostatic gate control of the sub-fin region and the corresponding parasitic conduction path are the largest concern for radiation hardness in FinFET technology. The high-Vth transistors exhibit the best irradiation performance across all bias conditions, showing a reasonably small change in off-state leakage current and Vth, while the low-Vth transistors exhibit a larger change in off-state leakage current. The “worst-case” bias condition during irradiation for both pull-down and pass-gate nMOSFETs in static random access memory is determined to be the on-state (Vgs = Vdd). We find the nMOSFET pull-down and pass-gate transistors of the SRAM bit-cell show less radiation-induced degradation due to transistor geometry and channel doping differences than the low-Vth transistor. Near-threshold operation is presented as a methodology for reducing radiation-induced increases in off-state device leakage current. In a 14-nm FinFET technology, the modeling indicates devices with high channel stop doping show the most robust response to TID allowing stable operation of ring oscillators and the SRAM bit-cell with minimal shift in critical operating characteristics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Towards Efficient Alternating Current Optimal Power Flow Analysis on Graphical Processing Units

We present a solution of sparse ACOPF analysis on GPU. In particular, we discuss the performance bottlenecks and detail our efforts to accelerate the linear solver, a core component of ACOPF that dominates the computational time. ACOPF solutions of two large-scale systems, synthetic Northeast (25,000 buses) and Eastern (70,000 buses) \cite{birchfield2017tamu-cases} on GPU show promising speed-up compared to CPU based solution using a state-of-the-art solver. To our knowledge, this is the first result demonstrating acceleration of sparse ACOPF on GPUs.

Power grid analysis, GPU↗