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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Microtube-Membrane Methodology for Electrochemical Synthesis and Study of Electroactive and Ionically Conductive Materials, and the Conductivity of MnO 2

A membrane-based methodology for electrochemical synthesis and study of electroactive and ionically conductive materials is described. The Li + -intercalation material MnO 2 was used to demonstrate this methodology. The membrane was a polymeric support containing monodisperse gold microtubes (diameter 600 nm) that span the thickness of the membrane. Bipolar electrochemical synthesis of MnO 2 , from Mn 2+ solutions, was conducted across this membrane, resulting in deposition of monodisperse, hemispherical MnO 2 particles at the open ends of the tubes on one face of the membrane. The resulting microtube/MnO 2 composite membrane makes a convenient construct for investigating the transport properties of the MnO 2 particles. This was accomplished by mounting the membrane in a U-tube cell, placing electrolyte solutions on either side, and driving an ionic current through the membrane. The ionic conductivity of MnO 2 was measured in this way, and found to be 40±10 μS cm -1 when LiCl or LiClO 4 solutions were used as the electrolyte. Finally, the mechanism of ionic conductivity through these MnO 2 particles is discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A novel methodology to integrate outcomes regarding perioperative pain experience into a composite score: Prediction model development and validation

Abstract Background An integrated score that globally assesses perioperative pain experience and rationally weights each component has not yet been developed. Methods A development dataset specific to adult Chinese patients undergoing orthopaedic surgery was obtained from PAIN OUT (1985 qualified patients of 2244). A more recent validation dataset obeying the same conditions was obtained from the Chinese Anaesthesia Shared‐database Platform (1004 qualified patients of 1032). Outcomes were assessed using the International Pain Outcomes Questionnaire (IPO‐Q), which comprises key patient‐level outcomes of perioperative pain management, including pain experience and perceptions of care. Using principal component analysis and regression models, a composite score (CS) was inferred to integrate pain experience. The discrimination of the CS for dissatisfaction and desire for more pain treatment was compared with that of the worst pain score. Results A CS was developed from the 12 items of the IPO‐Q regarding pain experience. The weight for calculating the CS was worst pain 11, least pain 17, time spent in severe pain 11, interference with activity in bed 9, interference with breathing deeply or coughing 10, interference with sleep 9, anxiety 12, helplessness 12, nausea 0, drowsiness 2, itch 5 and dizziness 2. In external validation, the CS indicated superior discrimination to the worst pain in predicting dissatisfaction ( p < 0.001) and desire for more pain treatment ( p < 0.001). Conclusions This study introduced a methodology to integrate outcomes regarding perioperative pain experience into a CS, which was based on the weight of each item. Significance This novel methodology sheds additional light on the riveting issue of carefully integrating several measures into a composite endpoint, which may be useful for quality improvement purposes when addressing the impact of a change in clinical practice.

Jiang, Bailin↗
DOE OSTI2024

A semi–automatic analytical methodology for characterizing the energy consumption of MRI systems using load duration curves

Background and purpose: Magnetic resonance imaging (MRI) scanners are a major contributor to greenhouse gas emissions from the healthcare sector, and efforts to improve energy efficiency and reduce energy consumption rely on quantification of the characteristics of energy consumption. The purpose of this work was to develop a semi-automatic analytical methodology for the characterization of the energy consumption of MRI systems using only the load duration curve (LDC). LDCs are a fundamental tool used across various fields to analyze and understand the behavior of loads over time. Methods: An electric current transformer sensor and data logger were installed on two 3T MRI scanners from two vendors, termed M1 (outpatient scanner) and M2 (inpatient/emergency scanner). Data was collected for 1 month (7/11/2023 to 8/11/2023). Active power was calculated, assuming a balanced three-phase system, using the average current measured across all three phases, a 480 V reference voltage for both machines, and vendor-provided power factors. An LDC was constructed for each system by sorting the active power values in descending order and computing the cumulative time (in units of percentage) for each data point. The first derivative of the LDC was then computed (LDC’), smoothed by convolution with a window function (sLDC’), and used to detect transitions between different system modes including (in descending power levels): scan, prepared-to-scan, idle, low-power, and off. The final, segmented LDC was used to measure time (% total time), total energy (kWh), and mean power (kW) for each system mode on both scanners. The method was validated by comparing mean power values, computed using the segmented 1-month LDC, for each nonproductive system mode (i.e., prepared-to-scan, idle, lower-power, and off) against power levels measured after a deliberate system shutdown was performed for each scanner (1 day worth of data). Results: The validation revealed differences in mean power values <1.4% for all nonproductive modes and both scanners. In the scan system mode, the mean power values ranged from 29.8 to 37.2 kW and the total energy consumed for 1 month ranged from 11 106 to 14 466 kWh depending on the scanner. Over the course of 1 month, the portion of time the scanners were in nonproductive modes ranged from 76% to 80% across scanners and the nonproductive energy consumption ranged from 8010 to 6722 kWh depending on the scanner. The M1 (outpatient) scanner consumed 99.9 and 183.9 kWh/day in idle mode for weekdays and weekends, respectively, because the scanner spent 23% more time proportionally in idle mode on the weekends. Conclusions: A semi-automatic method for quantifying energy consumption characteristics of MRI scanners was introduced and validated. This method is relatively simple to implement as it requires only power data from the scanners and avoids the technical challenges associated with extracting and processing scanner log files. Finally, the methodology enables quantitative evaluation of the power, time, and energy characteristics of MRI scanners in scan and nonproductive system modes, providing baseline data and the capability of identifying potential opportunities for enhancing the energy efficiency of MRI scanners.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Dot tracking methodology for background-oriented schlieren (BOS)

We propose here a dot tracking methodology for processing background-oriented schlieren (BOS) images. The technique improves the accuracy, precision and spatial resolution compared to conventional cross-correlation algorithms. Our methodology utilizes the prior information about the dot pattern such as the location, size and number of dots to provide near 100% yield even for high dot densities (20 dots/32 × 32 pixels) and is robust to image noise. Furthermore, we propose an improvement to the displacement estimation step in the tracking process, especially for noisy images, using a “correlation correction”, whereby we combine the spatial resolution benefit of the tracking method and the smoothing property of the correlation method to increase the dynamic range of the overall measurement process. We evaluate the performance of the method with synthetic BOS images of buoyancy-driven turbulence rendered using ray-tracing simulations, and experimental images of flow in the exit plane of a converging–diverging nozzle. The results show that the improved spatial resolution results in a better accuracy of the tracking method compared to correlation-based methods in regions with sharp displacement gradients, and the correlation correction step reduces the noise floor of the measurement, resulting in a fourfold improvement in the dynamic range.

42 ENGINEERING↗
DOE OSTI2020

ProZES: the methodology and software tool for assessment of assigned share of radiation in probability of cancer occurrence

ProZES is a software tool for estimating the probability that a given cancer was caused by preceding exposure to ionising radiation. ProZES calculates this probability, the assigned share, for solid cancers and hematopoietic malignant diseases, in cases of exposures to low-LET radiation, and for lung cancer in cases of exposure to radon. User-specified inputs include birth year, sex, type of diagnosed cancer, age at diagnosis, radiation exposure history and characteristics, and smoking behaviour for lung cancer. Cancer risk models are an essential part of ProZES. Linking disease and exposure to radiation involves several methodological aspects, and assessment of uncertainties received particular attention. ProZES systematically uses the principle of multi-model inference. Models of radiation risk were either newly developed or critically re-evaluated for ProZES, including dedicated models for frequent types of cancer and, for less common diseases, models for groups of functionally similar cancer sites. The low-LET models originate mostly from the study of atomic bomb survivors in Hiroshima and Nagasaki. Risks predicted by these models are adjusted to be applicable to the population of Germany and to different time periods. Adjustment factors for low dose rates and for a reduced risk during the minimum latency time between exposure and cancer are also applied. The development of the methodology and software was initiated and supported by the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) taking up advice by the German Commission on Radiological Protection (SSK, Strahlenschutzkommission). These provide the scientific basis to support decision making on compensation claims regarding malignancies following occupational exposure to radiation in Germany.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Radium-226 analysis methodology in Savannah River Site high activity waste matrices

Waste cleanup efforts currently underway at the Savannah River Site have created a need to characterize Radium-226 levels in the various high activity waste matrices currently in Site inventories. Here, the traditional method our laboratory used for analyzing Ra-226 in higher activity matrices was based on classic cation exchange methodology. Radiochemical separations were often initiated in remotely operated shielded analytical cells followed by additional hands-on separations in radiological hoods. Methodology based on IBC advanced technologies SuperLig 640 extractant, mounted in 3M Empore filter media has been developed to streamLine the radium analyses.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2018

Assessing I 2 S-LWR economic competitiveness using systematic differential capital cost evaluation methodology

One of the major factors impeding nuclear power plant (NPP) construction is their economics. In this study, a systematic differential economics evaluation approach was developed through the use of the Code of Accounts guidelines to assess the costs of nuclear power plants. The methodology, entirely based on publicly available data, may serve as a template to evaluate direct costs for reactors of any size and design at any stage of developments. In particular, this approach was used to assess the costs of the Integral Inherently Safe Light Water Reactor (I 2 S-LWR). The I 2 S-LWR is a design concept of a large (~1000 MWe) light water reactor. One of its key design features promoting inherent safety is implementation of an integral primary circuit configuration, which however necessitates a compact design of the core and primary circuit components. Through the methodology here presented, a representative loop PWR design was taken as a reference and the differential cost was estimated for each individual account based on the design difference, or similarity. Cost scaling techniques were applied to the accounts representing systems that differ from the ones of the reference PWR. Cost estimating techniques were used to evaluate cost of innovative components that are not part of standard PWR designs. By evaluating the cost difference of the I 2 S-LWR from the standard PWR, rather than the absolute cost, the uncertainty in the estimate is reduced. A similar approach was used by ORNL to estimate the cost of a Fluoride-salt High-temperature Reactor (FHR). A traditional four-loop PWR plant with a core thermal power of 3417 MWth (1144 MWe) was selected as the reference. Costs for that plant were prepared in 1978 by the Department of Energy (DOE) Energy Economics Data Base (EEDB), averaging actual cost incurred in the construction of several nuclear power plants (NPP), itemized with a great level of detail according to the Code of Accounts. This best estimate costs are denoted PWR12-BE. For each account, the cost of equipment, site labor and site material is provided. Industry experts at Westinghouse Electric Company performed a “sanity check” of the cost items, adjusting the cost of several items to match the current market and supply chain data. The detailed cost assessment of I 2 S-LWR was performed, systematically analyzing cost for each account, and applying the differential economics approach. First, Relative importance of each account, i.e., its contribution to the total cost was established, to help focus analysis on the most significant contributors. Moreover, the accounts describing components that are different than that of the PWR12-BE were identified. The integral configuration of the reactor has important implications on the cost of the reactor plant equipment (accounts 22x). Turbine generator equipment (Accounts 23x) is not believed to be much different than that of the reference design. I 2 S-LWR structures (Accounts 21x) mainly differ from that of a standard LWR as several buildings (containment building, shield building, annex building, waste processing building, fuel storage building) are integrated into a single building (nuclear island). Yardwork has a higher cost for the I 2 S-LWR, as the NI is partially below grade. On the other hand, due to its compact Nuclear Island footprint, I 2 S-LWR facilitates (and includes in its reference version) the use of seismic isolators, which contribute to reducing the direct cost. The total capital investment cost (TCIC), on the $/kW basis, of I 2 S-LWR is 5.84% lower than that of PWR12-BE, in spite of the lower power output of I 2 S-LWR. However, for the Western US (0.7 g), benefits of the seismic isolation are more pronounced, and the I 2 S-LWR total capital investment cost is 13.02% lower than that of PWR12-BE. If the I 2 S-LWR is compared to a PWR10-BE (traditional loop design, but scaled to the same power level as I 2 S-LWR), the savings are even higher, in the range 11.12%–17.89%. The analysis indicates that I 2 S-LWR has potential to offer an economically attractive design, with TCIC lower than that of a nuclear power plant based on a traditional loop PWR design. In other words, I 2 S-LWR design offers significantly enhanced safety, while at the same time improving economics. The differential economics approach developed in this paper can be used in identifying changes in cost of key components in order to improve the economics of a nuclear reactor design. The method can also help compare the economics of advanced Generation IV reactors and innovative water-cooled SMR (Small Modular Reactors) with respect to standard LWR technologies. In summary, the differential economics approach and can be used as a tool capable of helping stakeholder decisions.

Economic↗
DOE OSTI2020

Day-ahead photovoltaic power production forecasting methodology based on machine learning and statistical post-processing

A main challenge towards ensuring large-scale and seamless integration of photovoltaic systems is to improve the accuracy of energy yield forecasts, especially in grid areas of high photovoltaic shares. The scope of this paper is to address this issue by presenting a unified methodology for hourly-averaged day-ahead photovoltaic power forecasts with improved accuracy, based on data-driven machine learning techniques and statistical post-processing. More specifically, the proposed forecasting methodology framework comprised of a data quality stage, data-driven power output machine learning model development (artificial neural networks), weather clustering assessment (K-means clustering), post-processing output optimisation (linear regressive correction method) and the final performance accuracy evaluation. The results showed that the application of linear regression coefficients to the forecasted outputs of the developed day-ahead photovoltaic power production neural network improved the performance accuracy by further correcting solar irradiance forecasting biases. The resulting optimised model provided a mean absolute percentage error of 4.7% when applied to historical system datasets. Finally, the model was validated both, at a hot as well as a cold semi-arid climatic location, and the obtained results demonstrated close agreement by yielding forecasting accuracies of mean absolute percentage error of 4.7% and 6.3%, respectively. Finally, the validation analysis provides evidence that the proposed model exhibits high performance in both forecasting accuracy and stability.

42 ENGINEERING↗
DOE OSTI2024

A methodology for selection of solid desiccants in energy recovery ventilators

Controlling indoor humidity levels is essential for maintaining acceptable indoor air quality in buildings. The use of energy recovery ventilators (ERVs) is an energy-efficient way to regulate indoor air humidity. Fixed-bed regenerators and rotary wheels are widely used ERVs because of their high sensible and latent effectiveness. These ERVs are made of desiccant-coated substrates, which enable them to transfer moisture between the supply and exhaust air streams. However, the moisture transfer ability of ERVs depends on the physiochemical and sorption properties of desiccants. Extensive, full-scale experiments are required to determine the best desiccant material for these systems. This paper presents a simplified method of selecting suitable desiccant materials for ERVs. The methodology involves important characterization methods, literature correlations for performance prediction, and cost-effective testing methods prior to full-scale testing, and full-scale test methods are discussed in detail. Furthermore, the performance of a few newly derived materials is evaluated and compared with that of conventional desiccants such as silica gel and molecular sieves. The highest latent effectiveness was obtained for composite of super absorbent polymer (SAP) with potassium formate (SAP-HCO2K-50 %), all-polymer porous solid desiccant (APPSD) and metal organic framework (MOF)–MIL–101 (Cr), followed by activated carbon fibre felt (ACFF) Silica sol-LiCl30, SAP, silica gel, MOF–303, and molecular sieve. Researchers and manufacturers would benefit from the proposed methodology and presented data in developing new desiccant materials for ERV applications.

Energy recovery↗
DOE OSTI2024

Optical image analysis for graphene layer detection: Enhanced green channel methodology

Graphene, a material of increasing research interest, requires accurate layer identification due to its sensitivity to layer count. Existing methods for graphene layer number identification are either time-consuming or of low accuracy, with high-accuracy methods often requiring expensive processes. This paper aims to address this challenge by proposing a cost-effective and efficient approach. Specifically, the current work highlights only the green channel—one of the three primary color channels (red, green, blue) that make up an optical image—from images of exfoliated graphene flakes for layer count identification. A linear regression is performed between pixel position and substrate green channel value, and this effect is subtracted from the entire optical image to mitigate background effects. By storing the range of green channel values for each type of flake (monolayer, bilayer, or tri-layer) based on a few images, we establish thresholds for identifying different types of layers in a particular setup. Additionally, our methodology allows for flexible threshold tuning using a single reference image, enabling adjustment to changes in detection setup such as illumination level, magnification, or microscope used. Finally, demonstrating high accuracy and flexibility, this methodology presents a suitable technique for graphene layer number identification without the need for large datasets or expensive instruments.

2D materials↗
DOE OSTI2021

A simple and practical process modeling methodology for pressure swing adsorption

Although many dynamic models exist for the design and simulation of pressure swing adsorption (PSA) processes, these models involve the solution of a complex system of coupled partial differential equations. Process engineers need a simple, practical, and yet robust short-cut model that helps decide whether to implement a PSA system in a process flowsheet. This work presents a “virtual” moving bed modeling methodology that considers only mass and energy balances and adsorption isotherms to describe the cyclic steady state behavior of PSA systems. Similar to tray efficiencies in distillation calculations, adsorption efficiencies are further introduced to account for system “non-ideality.” Finally, a lab-scale air separation system is used to illustrate the application of this modeling methodology.

42 ENGINEERING↗
DOE OSTI2023

Methodology for physics-informed generation of synthetic neutron time-of-flight measurement data

Accurate neutron cross section data are a vital input to the simulation of nuclear systems for a wide range of applications from energy production to national security. The evaluation of experimental data is a key step in producing accurate cross sections. There is a widely recognized lack of reproducibility in the evaluation process due to its artisanal nature and therefore there is a call for improvement within the nuclear data community. This can be realized by automating/standardizing viable parts of the process, namely, parameter estimation by fitting theoretical models to experimental data. This automation effort could greatly benefit from a synthetic data resource. This work leverages problem-specific physics, Monte Carlo sampling, and a general methodology for data synthesis to generate unlimited, labelled experimental cross-section data that is statistically indistinguishable to the observed data. Heuristic and, where applicable, rigorous statistical comparisons to observed data support this claim. The demonstration is based on/limited to transmission measurements at Rensselaer Polytechnic Institute (RPI) and energy-differential cross sections in the resolved resonance region (RRR). An open-source software is published alongside this article that executes the complete methodology to produce high-utility synthetic datasets. The goal of this work is to provide an approach and corresponding tool that will allow the evaluation community to begin exploring more data-driven, ML-based solutions to long-standing challenges in the field.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

EIAMUO methodology for environmental assessment of the post-war housing estates renovation: Practical application in Seville (Spain)

This paper reports on the environmental impact assessment of a specific urban fabric: the housing estate. This urban-growth typology arose in the second half of the twentieth century to supply the existing needs of the time. It involved short-term processes, reduced costs, and lower comfort standards, which are far from present European guidelines. Currently, they represent situations of unsustainability in cities worldwide that are undergoing improvement. Here, the environmental impact assessment and minimization for urban organisms (EIAMUO) methodology is presented. This consists of a system of eco-indicators created specifically for estimating the impacts associated with these fabrics. Through its practical application, a snapshot of the current situation is achieved and the targets designed to minimize the environmental impact are proposed. - Highlights: • An environmental-impact minimization methodology for housing estates is proposed. • The paper presents a new definition for city analysis: urban organism. • The areas for the assessment are energy, water, materials and waste and atmosphere. • Energy and water areas determine most of the housing estate environmental behavior. • The building character prevails in the urban organism's environmental assessment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Measuring greenhouse gas emissions from international air travel of a country’s residents methodological development and application for Sweden

Highlights: • A new method for estimating a country's GHG emissions from international air travel. • A reliable method based on total statistics of departures and on surveys for distance to final destination. • Total emissions for Swedish residents' air travel increased by 61% between 1990 and 2014 • In 2014 Swedish residents air travel emissions was on par with emissions from Swedish car traffic - Abstract: Global civil aviation accounts for 4–5% of total greenhouse gas emissions and these emissions are increasing. In the absence of sufficiently effective global climate instruments, national instruments might be considered as a complement, in which case some way of allocating emissions from international air travel between countries is needed. The purpose of this paper is to develop an accounting method that reflects one country's greenhouse gas emissions from international air travel, and to apply this methodology to Sweden. The new methodology consists of three parts: the number of international air trips made by the country's residents; the average distance of these trips; and the greenhouse gas emissions per passenger km. For Sweden, data for 1990 to 2014 show an increase in the number of trips by Sweden's population of 3.6% per year, resulting in, on average, one international journey (round trip 5800 km) per capita in 2014. The average distance to the final destination has increased only marginally due to simultaneous growth in both long and short trips. However, global average greenhouse gas emissions per passenger km have decreased by 1.9% per year between 1990 and 2014. Because the increase in the number of their trips has outweighed the decrease in emissions per km, the total emissions from Swedish residents' international air travel have increased by 61% between 1990 and 2014. The total emissions from Swedish residents' air travel, including both CO{sub 2} and non-CO{sub 2}-effects, were 11 Mt CO{sub 2} equivalents in 2014, which is the same level as the emissions from Swedish car traffic. This type of reliable data is important when designing policies and for getting public support for new policies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Assessing the cumulative health effect following short term exposure to multiple pollutants: An evaluation of methodological approaches using simulations and real data

Highlights: • Correlated exposures’ cumulative effect is a challenging methodological issue. • Simulations indicated the use of exposure score as the least biased approach. • The main effects approach presented the poorest performance. • The adaptive LASSO performed well when correlation was low or moderate. Assessment of the cumulative effect of correlated exposures is an open methodological issue in environmental epidemiology. Most previous studies have applied regression models with interaction terms or dimension reduction methods. The combined effect of pollutants has been also evaluated through the use of exposure scores that incorporate weights based on the strength of the component-specific associations with health outcomes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Methodology for energy strategy to prescreen the feasibility of Ground Source Heat Pump systems in residential and commercial buildings in the United States

Geothermal resources have potential to reduce dependence on fossil fuels. The viability of geothermal heat pumps or ground source heat pumps (GSHPs) is significant as a potential alternative energy source with substantial savings potential. While the prospect of these systems is promising for energy efficiency, careful feasibility analysis is required before implementation. Here, this paper presents the results of evaluation of the application feasibility for GSHPs in buildings across seven climate zones in three United States regions. A comprehensive methodology is developed to measure the integrated feasibility of GSHPs using compiled data for energy use intensity, energy cost and design parameters. Four different feasibility metrics are utilized: ground temperature, outdoor weather condition, energy savings potential, and cost benefits. For each metric, a corresponding feasibility score system is developed. The defined integrated feasibility score classifies the locations into five different feasibility levels ranging from Fair (0–20), Moderate (21–40), Good (41–60), High (61–80), and Very High (81–100). Conclusions show the GSHP feasibility level is High for 3 sites, Good for 8 sites and Moderate for 4 sites. Through the methodology, it is possible to develop a practical energy strategy for more economic and sustainable GSHP systems at an early design stage in the various viewpoints of geometries, climate conditions, operational factors, and energy costs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Models implemented in the methodological approach to design the initial STEP first wall contour

The official Spherical Tokamak for Energy Production mission aims to demonstrate the ability to generate net electricity from fusion with the STEP Prototype Power plant. One of the key technological and engineering challenges in fusion power plants is managing the loads on the first wall within acceptable limits. Therefore, the conceptual design development of the STEP Prototype Power plant needs to be based on load estimates derived using legitimate plasma physics assumptions through dynamic and flexible tools. The current design foresees the STEP main chamber first wall to withstand steady-state heat loads of up to ~1 MW/m 2 , excluding critical regions expected to receive higher heat loads such as the baffle regions approaching the divertors. These critical areas will require ad hoc assessments and will be designed with the presence of limiters. This article focuses on the models and methodology adopted for designing the 2-D poloidal contour of the STEP first wall, based on the anticipated charged particle and radiation heat loads during normal operation. Firstly, the models adopted for calculating the charged particle and radiation heat loads are introduced. The first model is validated through benchmarking against the particle tracing code SMARDDA, while the second model is verified by comparing it with data from the MAST-U experiment. Secondly, the model used to design the 2-D first wall contour according to the heat loads is explained. We acknowledge that this preliminary design stage assumes certain simplifications, notably an axisymmetric geometry, for computational efficiency and clarity in presentation. It is understood that subsequent design phases will address the complexities of real-world engineering, including non-axisymmetric effects, transient plasma scenarios, and the impact of disruptions on the first wall design. Finally, an automatic procedure based on these models is presented for defining the 2-D poloidal contour of the STEP first wall to minimize heat loads, taking into account the need to radiate most of the alpha-particle and auxiliary heating power. Here, by providing an overview of the models, methodology, and an automatic procedure, this paper contributes to the design process of the STEP first wall, addressing the engineering challenges associated with fusion power plant development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

U.S. DOE NETL methodology for estimating the prospective CO 2 storage resource of shales at the national and regional scale

While the majority of shale formations will serve as reservoir seals for stored anthropogenic carbon dioxide (CO2), hydrocarbon-bearing shale formations may be potential geologic sinks after depletion through primary production. Here in this paper we present the United States-Department of Energy-National Energy Technology Laboratory (US-DOE-NETL) methodology for screening-level assessment of prospective CO 2 storage resources in shale using a volumetric equation. Volumetric resource estimates are produced from the bulk volume, porosity, and sorptivity of the shale and storage efficiency factors based on formation-scale properties and petrophysical limitations on fluid transport. Prospective shale formations require: (1) prior hydrocarbon production using horizontal drilling and stimulation via staged, high-volume hydraulic fracturing, (2) depths sufficient to maintain CO 2 in a supercritical state, generally >800 m, and (3) an overlying seal. The US-DOE-NETL methodology accounts for storage of CO 2 in shale as a free fluid phase within fractures and matrix pores and as an sorbed phase on organic matter and clays. Uncertainties include but are not limited to poorly-constrained geologic variability in formation thickness, porosity, existing fluid content, organic richness, and mineralogy. Knowledge of how these parameters may be linked to depositional environments, facies, and diagenetic history of the shale will improve the understanding of pore-to-reservoir scale behavior, and provide improved estimates of prospective CO 2 storage.

25 ENERGY STORAGE↗