Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “reporting tools”

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 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

φ meson production in ρ + Al, ρ + Au, d + Au , and 3 He + Au collisions at $\sqrt{s_{NN}}$ = 200 GeV

We report small nuclear collisions are mainly sensitive to cold-nuclear-matter effects; however, the collective behavior observed in these collisions shows a hint of hot-nuclear-matter effects. The identified-particle spectra, especially the φ mesons which contain strange and antistrange quarks and have a relatively small hadronic-interaction cross section, are a good tool to study these effects. The PHENIX experiment has measured φ mesons in a specific set of small collision systems p+Al, p+Au, and 3 He+Au, as well as d+Au at $\sqrt{s_{NN}}$=200 GeV. The transverse-momentum spectra and nuclear-modification factors are presented and compared to theoretical-model predictions. The comparisons with different calculations suggest that quark-gluon plasma may be formed in these small collision systems at $\sqrt{s_{NN}}$=200 GeV. However, the volume and the lifetime of the produced medium may be insufficient for observing strangeness-enhancement and jet-quenching effects. The comparison with calculations suggests that the main production mechanisms of φ mesons at midrapidity may be different in p+Al versus p/d/ 3 He+Au collisions at $\sqrt{s_{NN}}$=200 GeV. While thermal quark recombination seems to dominate in p/d/ 3 He+Au collisions, fragmentation seems to be the main production mechanism in p+Al collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Integrating Cambium Marginal Costs into Electric Sector Decisions: Opportunities to Integrate Cambium Marginal Cost Data into Berkeley Lab Analysis and Technical Assistance

NREL’s Cambium tool generates forward-looking simulations of marginal wholesale electricity costs associated with NREL’s Standard Scenarios. The scenarios include growing shares of variable renewable energy (VRE, i.e. wind and solar), among other power sector assumptions, between 2018 and 2050. The tool’s primary output—hourly costs at more than 130 balancing areas—could serve as public and transparent data source that supports electric-sector decision-making processes across the U.S. Berkeley Lab conducts a large range of analyses that use historical and forward-looking wholesale electricity prices to inform electric-sector decisions. In this report, Berkeley Lab uses its expertise to evaluate the Cambium cost data. We compare Cambium data with historical wholesale prices for the year 2018 and other modeled prices for the year 2030. We then present eight case studies in which Berkeley Lab researchers use Cambium data to replicate previous analyses based on other price datasets. We describe where primary findings and underlying key price dynamics align or differ, and highlight possible novel insights from the Cambium data. Finally, we qualitatively evaluate the suitability of Cambium costs in ten additional Berkeley Lab studies, though a direct comparison with alternative price data was not feasible at this time. The goal is to inform how electric-sector decision-makers and DOE program offices may be able to use this cohesive dataset, and to highlight what improvements to Cambium may make it even more useful.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Elastic Changepoint Detection for Globally-indexed Functional Time Series Data with Climate Applications

Changepoint detection is a vital tool in the application of climate data analysis. Numerous types of climate observation data are most properly represented by functional time series, implying a need for accurate changepoint detection methods applicable to functional time series data. Such data taken at a global scale often contain both spatial heterogeneity and dependence as well as phase (time) misalignment. In this report, we present methods which can detect spatially-dependent changepoints while allowing different estimates of change time and change strength depending on location. Additionally, we provide extensions to this spatially-predicted model which controls for phase variability among observations. Our methods provide the ability to detect a single change, or control for epidemic changes (where a “return-to-normal” change is more likely to be detected than the initial change). We showcase results analyzing the June 1991 eruption of Mt. Pinatubo, where our methods demonstrate the ability to accurately detect both single and epidemic changepoints even in the presence of strong seasonal variability. We find that our spatially-predicted model improves the detection of relevant changepoints versus methods which do not take spatial information into account, and we find that controlling for phase variability helps to control the false discovery rate during the detection process.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Probabilistic Multi-Hazard Performance Assessment of Concrete Structures in Nuclear Installations

Concrete structures in nuclear installations are subject to time-dependent degradation mechanisms that can deteriorate their physical and mechanical properties, potentially exacerbating the risk of structural failure under external forces such as a seismic event. Previous research has extensively investigated the seismic response of nuclear concrete structures and the associated risk, as well as their effect on structural components safety margins. However, substantial work is still necessary to incorporate concrete aging effects into such evaluations. In fact, most models in the literature assume pristine concrete conditions and do not account for the impact of aging on the structural components’ fragility curves. This work identifies relevant time-dependent degradation mechanisms and provides simplified models to predict the the evolution of key material properties based on data from the literature. Namely, this work focuses on the aging effects of corrosion, alkali–silica reaction (ASR), and irradiation on reinforced concrete within US Department of Energy (DOE) nuclear facilities and nuclear power plants (NPP) structures. Furthermore, degradation models based on literature data are presented that define the relationship between probabilistic material properties and the concrete’s age. In this work, sampled material properties served as input for a simplified finite element model (FEM) of a critical nuclear structural system, with the output of the FEM being the seismic response for a given ground motion. The results of the FEM were then used within a probabilistic performance assessment with a statistically significant number of samples. The research presented herein addresses the detrimental effects of hazards caused by natural phenomena on deteriorated concrete elements of nuclear installations. This work directly benefits the safety analysis performed on US DOE/ National Nuclear Security Administration (NNSA) nuclear facilities located in areas prone to seismic activity. The results presented herein could aid in the improvement of DOE-STD-1020, the DOE Standard that addresses seismic risk analysis and capacity evaluation in DOE facilities. DOE-STD-1020 refers to the requirements in American Society of Civil Engineers (ASCE) 4-98, now superseded by ASCE 4-16, that shall be met in performing dynamic response analyses and generating in-structure response spectra, provided that such requirements are consistent with the requirements of ASCE/Structural Engineering Institute (SEI) 43-05. Moreover, the results presented herein could also aid in the updating of section C3.1.1. of ASCE 4-16 to account for the effects of aging on the stiffness of reinforced elements and American Concrete Institute (ACI) 349.3R-18, “Report on Evaluation and Repair of Existing Nuclear Safety-Related Concrete Structures.” Ultimately, this work can assist the risk assessment of potential lifetime extension of the existing US commercial nuclear fleet (light water reactors) and the safety analysis of the emerging advanced nuclear reactors. The proposed proof-of-concept methodology employs open-source DOE computational tools and is transferable to commercial software commonly used by engineering firms.

42 ENGINEERING↗
DOE OSTI2021

Energy Arbitrage: Comparison of Options for use with LWR Nuclear Power Plants

Arbitrage is the opportunistic buying and selling of a commodity during local pricing valleys and peaks respectively to maximize economic value. This report evaluates options for energy arbitrage integrated with existing light water reactor (LWR) nuclear power plants (NPPs) where nuclear energy could be stored in a variety of forms and later recovered to generate electrical power during periods when grid electricity demand and pricing are high. The forms of energy storage examined in this report include the potential value of batteries, hydrogen, and thermal energy storage for coupling with nuclear power. Various large demand response options are also analyzed, including the production of liquid nitrogen via air separation and liquefaction, liquefaction of hydrogen, compressed hydrogen, and the cryogenic capture of CO2. Demand response refers to dispatchable loads that can cycle up or down depending on-grid electricity demand to aid in balancing the grid. Large demand response options could dispatch to aid nuclear power stations in avoiding power turndowns by providing an alternate disposition for electrical energy by producing marketable products (e.g., liquid nitrogen, hydrogen, or captured CO2). Static conditions were chosen and analyzed in this report for each option. Dynamic operation or optimization of energy arbitrage or demand response are out of scope for this report. The analysis is based on storage systems with discharge capacities of 500 MW for which various durations of storage and costs of charging (electricity cost) are examined. While the value of thermal energy to an industrial user for flexible plant operations has been previously proven as a business case, this report evaluates costs of hydrogen energy storage and leading thermal energy storage options, and large demand response loads that could be integrated with LWRs in comparison to utility-scale battery storage for use of off-peak nuclear energy. Compilation of this information will be used by the Idaho National Laboratory (INL) RAVEN/HERON systems integration and economics tool to evaluate thermal energy dispatch to industrial users. Relative ranking of energy storage options was done using a levelized cost of storage (LCOS) metric which calculates a rough breakeven cost for the system, taking into account the capital and operating costs as well as the revenue from arbitrage. Table ES1 below shows the LCOS for each of the energy storage options considered. First, in the table, lithium iron (Fe) phosphate batteries are listed as the base case for comparison against the other options. Next is hydrogen storage where most of the hydrogen analyses assumed the hydrogen to be produced using solid oxide electrolytic cell (SOEC) high temperature steam electrolysis (HTSE). The others used existing models of polymer electrolyte membrane (PEM) low temperature electrolysis to produce hydrogen. HTSE performance parameters and costs were taken from existing INL models. Various means were assumed to convert the hydrogen to electricity, including PEM fuel cells (FCs) and a gas turbine mixed in a 30 vol% mixture with natural gas. Physical storage (pressure vessels) and geological storage (natural underground features) were used to store the hydrogen as noted. Geological storage is more economical, but the locations are limited because of the requirement for pre-existing geological formations that will support storage. Thermal energy storage (TES) options were also analyzed including electro-thermal energy storage (ETES) and four different liquid sensible heat TES storage media as noted (Hitec, Hitec XL, Therminol-66, and Dowtherm A). The ETES process considered was modified using existing public documentation on an Echogen process and uses a separate supercritical CO2 charge and discharge cycle with sand as the heat storage media.

25 ENERGY STORAGE↗
DOE OSTI2025

Advanced Interactive 3D Visualization Tool for Customizable Analyses of Tomography Datasets in Material Science

Current methods for visualizing and analyzing 3D tomography datasets in materials science often lack the interactivity and depth required for detailed structural insights. This limitation restricts a researchers' ability to accurately interpret complex data, which is critical for advancing material innovations and understanding structural properties. To address this issue, we have developed a novel, web-based interactive 3D visualization and analysis tool from the Trame framework that offers customizable features to enhance data interpretability. The tool allows users to adjust parameters such as visible range, slice planes, data rotation, and layering, providing a more detailed and dynamic view of complex structures. Its user-friendly web interface increases the accessibility and ease of use for both novice and experienced researchers, to visualize large volumetric datasets. The tool supports a diverse range of data formats, making it versatile for various research applications. Unique capabilities include real-time data manipulation, automated feature detection, context-sensitive feedback, and real-time volume calculations and distributions per sliced region or layer, alongside the ability to quickly generate high-quality screenshots and videos for presentations and reports. These advancements offer a comprehensive solution for enhanced 3D data exploration, significantly improving the analysis process and communication of results in materials science.

36 - MATERIALS SCIENCE↗
DOE OSTI2020

2020 State of the Science Report, Chapter 12: Adaptive Management Related to Marine Renewable Energy

As the marine renewable energy (MRE) industry is rapidly ramped up from single devices to commercial-scale deployments, developers and regulators will need evidence of the environmental effects of MRE to inform project development and consenting/permitting (hereafter consenting) processes. Uncertainty surrounding the potential impacts of novel RE technologies on sensitive marine animals, habitats, and ecosystem processes means that even robust baseline environmental information cannot comprehensively address all pre-deployment knowledge gaps. Tools and practical approaches are needed to help with the sustainable development of the industry. Adaptive management (AM), also referred to as learning by/while doing, enables projects to be deployed incrementally, despite uncertainty, in a way that prevents unacceptable harm to the marine environment. If rigorously implemented, this approach may provide a reliable mechanism for closing knowledge gaps, thereby retiring risks for future MRE developments. This chapter explores and suggests a pathway for applying a passive approach to AM for the consenting of single devices and array-scale MRE projects. Complementary information is available online at https://tethys.pnnl.gov/state-of-thescience-2020 -supplementaryadaptive-management. https://tethys.pnnl.gov/publications/state-of-the-science-2020-chapter-12-adaptive-management

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Ecosystems and Networks Integrated with Genes and Molecular Assemblies (ENIGMA): Molecular and Computational Technologies for Environmental Microbiology (Final Scientific/Technical Report)

The ENIGMA science focus area (SFA) is a multi-disciplinary, multi-institutional research effort focused on addressing foundational knowledge gaps in environmental microbial communities by studying groundwater and sediment microbiomes in the shallow subsurface at the contaminated Oak Ridge Reservation (ORR). We seek to discover and characterize the reciprocal interactions between the microbial communities and the geochemical and geophysical parameters of the shallow subsurface within the contamination plume. The primary goal of this subcontract was to develop experimental and computational tools to advance our understanding of microbial adaptation and community assembly in contaminated environments, with specific efforts in high-throughput genomic methods, microbial ecology tools, and studies of heavy metal contamination impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Gateway Cities Unplugged: (em)Powering Affordable Housing (Final Technical Report)

The Gateway Cities Unplugged: (em)Powering Affordable Housing (the “Project”) was launched to address a critical challenge in the U.S. building and energy sectors: enabling multifamily buildings especially those serving low and moderate‑income (LMI) communities to actively support grid modernization through Grid‑Interactive Efficient Buildings (GEB). Multifamily housing represents a large share of national building energy consumption, yet the sector faces persistent barriers to adopting advanced load flexibility technologies, including capital constraints, aging infrastructure, and limited access to demand‑side management tools. This Project sought to overcome those barriers by defining, evaluating, and designing commercially viable GEB technology packages for six representative multifamily properties across Massachusetts, Connecticut, and New York.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Dark Energy Studies with LSST using the Photon Simulator (Final Report)

This grant funded the development and dissemination of the Photon Simulator (PhoSim) for the purpose of studying dark energy at high precision with the upcoming Large Synoptic Survey Telescope (LSST) astronomical survey. The work was in collaboration with the Dark Energy Science Collaboration (DESC). Several detailed physics improvements were made in the optics, atmosphere and sensor, a number of validation studies were performed, and a significant number of usability features were implemented. Future work in DESC will use PhoSim as the image simulation tool for data challenges used by the analysis groups.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Single-step conversion of ethanol into n-butene-rich olefins over metal catalysts supported on ZrO 2 -SiO 2 mixed oxides

With airlines committed to drastically reduce their carbon footprint by 2050, producing jet fuel from renewable ethanol is of particular interest. Here we reported on an Ag/ZrO 2 /SBA-16 catalyst that is very effective for directly converting ethanol into to n-butene-rich olefins jet fuel precursors (i.e., 88% at full conversion). Here, we report on a Cu/ZrO 2 /SBA-16 catalyst that presents remarkable olefins selectivity (i.e., 89% at 96% conversion) and enhanced stability as compared to Ag/ZrO2/SBA-16 catalyst. Under severe operating conditions a conversion loss < 10% was observed with the Cu/ZrO 2 /SBA-16 catalyst as compared to a 50% loss of conversion with the Ag/ZrO 2 /SBA-16 catalyst. Combined experimental and computational tools revealed that replacing Ag with Cu shifts the reaction pathway of crotonaldehyde hydrogenation from 1,3-butadiene (i.e., coke precursor) production to butyraldehyde formation. Experiments conducted with 4%Cu/4%ZrO 2 supported on SBA-16, dealuminated zeolite Beta, and aluminum silicate revealed the performance and stability advantage of the SBA-16-supported catalyst.

09 BIOMASS FUELS↗
DOE OSTI2023

Development of a Structure for Lossless Ion Manipulations (SLIM) High Charge Capacity Array of Traps

Enhancing the sensitivity of low abundance ions in a complex mixture without sacrificing experiment throughput is highly desirable. This work demonstrates a way to greatly improve the sensitivity of ion mobility (IM) selected ions by accumulating them in an array of high-capacity ion traps located inside a novel structures for lossless ion manipulations ion mobility spectrometer (SLIM-IMS) module. The array of ion traps used in this work consisted of seven independently controllable traps. Each trap was 386 mm long and possessed a charge capacity of ~4.5×10 8 charges, with a linear range extending to ~2.5×10 8 charges. Each ion trap could be used to extract a peak (or ions over a mobility range) from an ion mobility separation based on arrival time. Ions could be stored without losses for long times (>100 s) and then released all at once or one trap at a time. It was possible to accumulate large ion populations by extracting and storing ions over repeated IM separations. We report enrichment of up to seven individual ion distributions could be performed using the seven independently controllable ion traps. Additionally, the ion trapping process effectively compressed ion populations into narrow peaks, which provides a greatly improved basis for subsequent ion manipulations. The array of high charge-capacity ion traps provides a flexible addition to SLIM and a powerful tool for IMS-MS applications requiring high sensitivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Automated Gold Nanorod Spectral Morphology Analysis Pipeline

The development of a colloidal synthesis procedure to produce nanomaterials with high shape and size purity is often a time-consuming, iterative process. This is often due to quantitative uncertainties in the required reaction conditions and the time, resources, and expertise intensive characterization methods required for quantitative determination of nanomaterial size and shape. Absorption spectroscopy is often the easiest method for colloidal nanomaterial characterization. However, due to the lack of a reliable method to extract nanoparticle shapes from absorption spectroscopy, it is generally treated as a more qualitative measure for metal nanoparticles. This work demonstrates a gold nanorod (AuNR) spectral morphology analysis tool, called AuNR-SMA, which is a fast and accurate method to extract quantitative structural information from colloidal AuNR absorption spectra. To demonstrate the practical utility of this model, we apply it to three distinct applications. First, we demonstrate this model's utility as an automated analysis tool in a high-throughput AuNR synthesis procedure by generating quantitative size information from optical spectra. Second, we use the predictions generated by this model to train a machine learning model to predict the resulting AuNR size distributions under specified reaction conditions. Third, we apply this model to spectra extracted from the literature where no size distributions are reported and impute unreported quantitative information on AuNR synthesis. This approach can potentially be extended to any other nanocrystal system where absorption spectra are size dependent, and accurate numerical simulation of absorption spectra is possible. In addition, this pipeline could be integrated into automated synthesis apparatuses to provide interpretable data from simple measurements, help explore the synthesis science of nanoparticles in a rational manner, or facilitate closed-loop workflows.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Realizing High-Accuracy Low-Cost Measurement and Verification for Deep Cost Savings (BPA Cost Share CRADA)

Developed practitioner workflows that integrate advanced M&V tools with supplementary automated routines for non-routine adjustments and for quantification of savings uncertainty to indicate rigor. Demonstrated these workflows with Seattle City Light, in collaboration with their implementers and evaluators – determine labor and time/cost savings, and uncertainty of the results obtained. Engaged the Pacific Northwest regulatory community to determine acceptance criteria for the required accuracy and reporting of advanced whole-building M&V. Documented the findings to facilitate broad industry uptake of the solutions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Relationship Extraction: Automatic Information Extraction and Organization for Supporting Analysts in Threat Assessment

In order for analysts to be able to do their work, they sift through hundreds, thousands, or even millions of documents to make connections between entities of interest. This process is time consuming, tedious, and prone to potential error from missed connections or connections made that should not have been. There exist many tools in natural language processing, or NLP, to extract information from documents. However, when it comes to relationship extraction, there has been varied success. This project began with a goal to solve the relationship extraction problem which developed into a deeper understanding of the problem and the associated challenges for solving this problem on a general scale. In this report, we explain our research and approach to relationship extraction, identify other auxiliary problems in NLP that provide additional challenges to solving relationship extraction generally, explain our analysis of the current state of relationship extraction, and postulate future work to address these problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Batteries Included: Top 10 Findings from Berkeley Lab Research on the Growth of Hybrid Power Plants in the United States

One of the most important electric power system trends of the 2010s was the rapid deployment of wind turbines and photovoltaic arrays, but a twist for the 2020s may be the rapid deployment of ‘hybrid’ generation resources. Hybrid power plants typically combine solar or wind (or other energy sources) with co-located storage. While hybridization helps to ease the challenge of balancing variable supply and demand, its relative novelty means that research is needed to facilitate integration and promote innovation. Combining the characteristics of multiple energy, storage, and conversion technologies poses complex questions for grid operations and economics. Project developers, system operators, planners, and regulators would benefit from better data, methods, and tools to estimate the costs, values, and system impacts of hybrid projects. This publication showcases some of Berkeley Lab’s robust research program intended to support private- and public-sector decision-making about hybrid plants in the United States. Our short briefing summarizes articles that we published between 2020 and 2022, links to the in-depth reports, and provides contact details for further engagement on the specific research topics: Growth: Developer interest in hybrid power plants is strong and growing Price vs. Value: PV+storage hybrids have low PPA prices and high value in some regions Market Drivers: Solar hybridization is driven by tax credits and other benefits Configuration Choices: Market prices have incentivized shorter duration batteries with PV Capacity Value: The capacity contribution of a hybrid is less than the sum of its parts Ancillary Services: AS markets are a valuable yet fleeting option for hybrids Market Participation: Hybrids can more flexibly engage with electricity markets Operations: The power system value of hybrids depends on how they are operated Distributed Hybrids: Growth of customer-sited PV+storage hybrids offers new opportunities Future Research: Where next? Priority areas for hybrid power research.

25 ENERGY STORAGE↗
DOE OSTI2023

An Integrated Framework for Risk Assessment of Safety-related Digital Instrumentation and Control Systems in Nuclear Power Plants: Methodology Refinement and Exploration

This report documents activities performed by Idaho National Laboratory (INL) during Fiscal Year (FY) 2023 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk Informed Systems Analysis (RISA) Pathway, digital instrumentation and control (DI&C) risk assessment project. In FY 2019, the RISA Pathway initiated a project to develop a risk assessment strategy for delivering a technical basis to support effective, and secure DI&C technologies for digital upgrades/designs. A risk assessment-informed framework was proposed for this strategy, which aims to (1) provide a best-estimate, risk informed capability to quantitatively estimate the safety margin obtained from plant modernization, especially for safety-related DI&C systems, (2) support and supplement existing risk informed DI&C design guides by providing quantitative risk information and evidence, (3) offer a capability of design architecture evaluation of various DI&C systems, (4) assure the long-term safety and reliability of safety-related DI&C systems, and (5) reduce uncertainty in costs and support integration of DI&C systems in the plant. To achieve these technical goals, the LWRS-developed framework provides a means to address relevant technical issues by: (1) defining a risk informed analysis process for DI&C upgrade that integrates hazard analysis, reliability analysis, and consequence analysis, (2) applying risk informed tools to address common cause failures (CCFs) and quantify corresponding failure probabilities for DI&C technologies, particularly software CCFs, (3) evaluating the impact of digital failures at the component level, system level, and plant level, and (4) providing insights and suggestions on designs to manage the risks, thus to support the development and deployment of advanced DI&C technologies in nuclear power plants (NPPs). Adding diversity within a system or components is the primary means to eliminate and mitigate CCFs, but diversity also increases system complexity and may not address all sources of systematic failures. Optimization of diversity and redundancy applications for the safety-critical DI&C systems remains a challenge. To deal with the technical issues in addressing potential software CCFs in safety-related DI&C systems of NPPs and supporting relevant design optimization, the proposed framework provides: (a) A best-estimate, risk informed capability to address new technical digital issues quantitatively, focusing on software CCFs in safety-related DI&C systems of NPPs; (b) A common and a modularized platform for DI&C designers, software developers, cybersecurity analysts, and plant engineers to predict and prevent risk in the early design stage of DI&C systems; (c) Technical bases and risk informed insights to assist users address the risk informed alternatives for evaluation of CCFs in safety-related DI&C systems of NPPs; and (d) A risk informed tool that offers a capability of design architecture evaluation of various DI&C systems to support system design decisions in diversity and redundancy applications. The research and development efforts of this project in FY 2023 are focused on refining current methods on software CCF modeling and estimation and exploring additional innovative approaches to risk assessment of DI&C systems to enable a more comprehensive and complete assessment of various safety-related DI&C design architectures. The primary audience of this report are DI&C designers, engineers, and probabilistic risk assessment (PRA) practitioners. This includes stakeholders, such as the nuclear utilities and regulators who consider the deployment and upgrade of DI&C systems, DI&C software developers and reviewers, and cybersecurity specialists. It should be noted that all the analyses are performed for the demonstration of the methodology, not for the evaluation of an actual digital control system. Results are obtained based on limited design information and testing data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Final Report: Enhanced Algal Production of CA for Improved Atmospheric Delivery of CO2 To Ponds

Technologies that enable direct-air-capture (DAC) of CO2 and eliminate the need for a CO2 capture, storage, and distribution system would significantly reduce the cost of algal production, and greatly increase the volume of algae biomass that can be produced by enabling algae farms to be located anywhere. Such technologies include cultivation under high alkalinity/high pH conditions, which increase the driving force for CO2 absorption, and development of genetic tools and genetically engineered strains to decorate the surface of the algae with carbonic anhydrase (CA), enable secretion of CA by the algae, or more generally boost the performance of the carbon concentrating mechanism (CCM).

09 BIOMASS FUELS↗