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At least 649 records · Page 36

Understanding the structure and mechanism of Na + diffusion in NASICON solid-state electrolytes and the effect of Sc- and Al/Y-substitution

NASICON (sodium superionic conductor) based ceramics are one of the most promising classes of solid-state electrolytes for all-solid-state batteries. However, the mechanism of sodium ion diffusion is not understood in great detail since there is still a discrepancy between reported average structure models, local structures, and the number and position of sodium sites. To close this gap, we investigate the underlying diffusion mechanism and structural changes governing the Na + transport in Na 3.4 Zr 2 Si 2.4 P 0.6 O 12 using quasielastic neutron scattering (QENS) and powder X-ray diffraction (XRD). In the temperature range from 298 K to 640 K, the correlations between structural changes of a monoclinic C2/c to rhombohedral R $\bar{3}$c phase transition and the result of ion diffusion are investigated. The analysis of the quasielastic neutron scattering data reveals two quasielastic components corresponding to the Chudley-Elliott jump-diffusion model. It clearly shows two different Na + diffusion processes, local and long-range, on two different time and length scales and allows calculations of their corresponding activation energies. Additionally, the effects of Sc 3+ and Al 3+ /Y 3+ aliovalent substitution of Zr 4+ ions on the crystal structure and Na + diffusion are also studied. We can distinguish a local, chain, and cross-chain diffusion mechanism based on correlated QENS and XRD comparison of relevant nearest crystallographic Na–Na distances. The results reveal that the Na + diffusion in these NASICONs is three-dimensional and can provide guidelines on how dopants and changes in the crystal structure can affect the Na + conductivity.

25 ENERGY STORAGE↗

Advanced single permanent magnet axipolar ironless stator ac motor for electric passenger vehicles

A program was conducted to design and develop an advanced-concept motor specifically created for propulsion of electric vehicles with increased range, reduced energy consumption, and reduced life-cycle costs in comparison with conventional systems. The motor developed is a brushless, dc, rare-earth cobalt, permanent magnet, axial air gap inductor machine that uses an ironless stator. Air cooling is inherent provided by the centrifugal-fan action of the rotor poles. An extensive design phase was conducted, which included analysis of the system performance versus the SAE J227a(D) driving cycle. A proof-of-principle model was developed and tested, and a functional model was developed and tested. Full generator-level testing was conducted on the functional model, recording electromagnetic, thermal, aerodynamic, and acoustic noise data. The machine demonstrated 20.3 kW output at 1466 rad/s and 160 dc. The novel ironless stator demonstated the capability to continuously operate at peak current. The projected system performance based on the use of a transistor inverter is 23.6 kW output power at 1466 rad/s and 83.3 percent efficiency. Design areas of concern regarding electric vehicle applications include the inherently high windage loss and rotor inertia.

Beauchamp, E. D.↗

Features and applications of the Groove Analysis Program (GAP)

An IBM Personal Computer (PC) version of the Groove Analysis program (GAP) was developed to predict the steady state heat transport capability of an axially grooved heat pipe for a specified groove geometry and working fluid. In the model, the capillary limit is determined by the numerical solution of the differential equation for momentum conservation with the appropriate boundary conditions. This governing equation accounts for the hydrodynamic losses due to friction in liquid and vapor flows and due to liquid/vapor shear interaction. Back-pumping in both 0-g and 1-g is accounted for in the boundary condition at the condenser end. Slug formation in 0-g and puddle flow in 1-g are also considered in the model. At the user's discretion, the code will perform the analysis for various fluid inventories (undercharge, nominal charge, overcharge, or a fixed fluid charge) and heat pipe elevations. GAP will also calculate the minimum required heat pipe wall thickness for pressure containment at design temperatures that are greater than or lower than the critical temperature of the working fluid. This paper discusses the theory behind the development of the GAP model. It also presents the many useful and powerful capabilities of the model. Furthermore, a correlation of flight test performance data and the predictions using GAP are presented and discussed.

Ku, Jentung↗

Technology Estimating 2: A Process to Determine the Cost and Schedule of Space Technology Research and Development

As a leader in space technology research and development, NASA is continuing in the development of the Technology Estimating process, initiated in 2012, for estimating the cost and schedule of low maturity technology research and development, where the Technology Readiness Level is less than TRL 6. NASA' s Technology Roadmap areas consist of 14 technology areas. The focus of this continuing Technology Estimating effort included four Technology Areas (TA): TA3 Space Power and Energy Storage, TA4 Robotics, TA8 Instruments, and TA12 Materials, to confine the research to the most abundant data pool. This research report continues the development of technology estimating efforts completed during 2013-2014, and addresses the refinement of parameters selected and recommended for use in the estimating process, where the parameters developed are applicable to Cost Estimating Relationships (CERs) used in the parametric cost estimating analysis. This research addresses the architecture for administration of the Technology Cost and Scheduling Estimating tool, the parameters suggested for computer software adjunct to any technology area, and the identification of gaps in the Technology Estimating process.

Cole, Stuart K.↗

Observational window effects on multi-object reverberation mapping

ABSTRACT Contemporary reverberation mapping campaigns are employing wide-area photometric data and high-multiplex spectroscopy to efficiently monitor hundreds of active galactic nuclei (AGNs). However, the interaction of the window function(s) imposed by the observation cadence with the reverberation lag and AGN variability time-scales (intrinsic to each source over a range of luminosities) impact our ability to recover these fundamental physical properties. Time dilation effects due to the sample source redshift distribution introduce added complexity. We present comprehensive analysis of the implications of observational cadence, seasonal gaps, and campaign baseline duration (i.e. the survey window function) for reverberation lag recovery. We find that the presence of a significant seasonal gap dominates the efficacy of any given campaign strategy for lag recovery across the parameter space, particularly for those sources with observed-frame lags above 100 d. Using the Australian Dark Energy Survey as a baseline, we consider the implications of this analysis for the 4MOST/Time-Domain Extragalactic Survey campaign providing concurrent follow-up of the Legacy Survey of Space and Time deep-drilling fields, as well as upcoming programmes. We conclude that the success of such surveys will be critically limited by the seasonal visibility of some potential field choices, but show significant improvement from extending the baseline. Optimizing the sample selection to fit the window function will improve survey efficacy.

79 ASTRONOMY AND ASTROPHYSICS↗

Considerations regarding the Use of Computer Vision Machine Learning in Safety-Related or Risk-Significant Applications in Nuclear Power Plants

With the advancements made to date in the field of artificial intelligence (AI), significant potential exists to utilize AI capabilities for nuclear power plant (NPP) applications. AI can replicate human decision making and it is usually faster and more accurate than humans. For implementations that impact critical NPP applications (e.g., safety-related or non-safety systems that potentially affect overall plant risk), a deeper safety analysis of the AI methods is necessary. AI applied to NPP operations could resemble the use of digital I&C (DI&C) because such applications involve digital computer hardware and custom-designed software that input plant data, execute complex software algorithms, and output the results to a system or licensed human operator to potentially provoke an action. For AI methods to be compliant with current safety requirements for DI&C, AI compatibility must be evaluated, and AI-related gaps may exist that prevent the prompt deployment of AI in NPPs. This effort aims to evaluate how example AI technologies align with the DI&C safety framework, and discusses how they could be analyzed, modeled, tested, and validated in a manner similar to typical DI&C technologies. Because AI is a broad field that encompasses areas such as machine learning (ML), natural language processing, and computer vision, this research focused on a subset of methods categorized as the computer vision ML (CVML) methods. This report explores two CVML use cases, gauge reading and fire watch, considered relevant to the DI&C standards, as they could play a safety-critical role. For the gauge reading use case, a CVML-enabled technology that can read gauges at oblique angles is utilized. For the fire watch use case, a CVML-enabled technology is utilized that migrates fire watch from a manual (human) approach to automated fire detection. These use cases are mainly intended to give context to the CVML system discussion. This effort assumes the worst-case scenario, with the CVML system being used to replace a safety-related or risk-significant system, thus requiring evaluation. Evaluating CVML against most of the relevant safety requirements for DI&C yielded several CVML-specific considerations due to the uniqueness of its characteristics in comparison with typical DI&C systems. For example, CVML models often employ commonly used (open-source) datasets, and it is not always possible to determine the level of overlap among open-source datasets. Therefore, the independence of the developed CVML models when demonstrating diversity is questionable, therefore creating vulnerability to common cause failure (CCF). The design verification process is also impacted since the data overlap could result in overestimation of the software validation and verification (V&V) performance results. Section 2 of this report evaluates a list of the identified CVML-specific characteristics and discusses the resulting considerations and potential solutions in the context of each referenced requirement. A summation is provided in Section 3. This report is not to be used as a guideline. It was developed to identify and consider issues in the implementation of ML technologies used to augment activities that may have a bearing on plant operation. The report draws parallels to the use of DI&C technologies, for which many standards are available to guide their use in nuclear plant operation. It considers the technologies and some of the potential implications of their use in safety-related applications but is not intended to address regulatory or licensing related issues.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Mechanical Loads on Spent Nuclear Fuel in the General 30 cm Package Drop Scenario

The U.S. Department of Energy Office of Nuclear Energy (DOE-NE) Spent Fuel and Waste Science & Technology (SFWST) research program is guided by the high-level goal of closing prioritized knowledge gaps related to spent nuclear fuel (SNF) storage and transportation, which are summarized by Saltzstein et al. (2020). One of the high-priority knowledge gaps is the identification and quantification of mechanical loads that are expected to affect SNF during normal conditions of transportation and storage to inform the range of physical SNF test programs. This report uses modeling and analysis methods to estimate the mechanical loads on spent nuclear fuel (SNF) in the general 30 cm package drop scenario. The drop scenario assumes impact limiters are in place in the transportation configuration and the impact surface is perfectly rigid. The goal of this analysis is to consider the universe of potential mechanical loading conditions that can happen to SNF and present the results in a manner that is useful for materials testing, decision making, and regulatory rule making purposes. This study uses validated finite element models and methods to perform a broad parametric study of key variables that can affect the mechanical loads on SNF during a hypothetical package free drop scenario. Physical drop test data from a cask and fuel assembly drop test campaign is the basis for model validation. Additionally, the results of the parametric study are used to inform a damage model, which uses multiple nonlinear regression to estimate the relationships between input variables and output response. The parametric finite element analyses consider thousands of input variable combinations, while the damage model estimates millions of combinations. The breadth of this study provides confidence that the potential range of mechanical loads that SNF might experience during the general 30 cm package drop scenario are characterized well enough to consider this knowledge gap closed. While this report documents the overall peak values calculated in this study, the 95 th percentile values, the histograms, and the observed trends are equally important. This study covered a large range of SNF temperatures, room temperature to 300°C, and burnups, 10 GWd/MTU to 62 GWd/MTU. Each temperature and burnup combination has a different cladding yield strain, so it is more meaningful to summarize the calculated cladding strain response as its factor of safety, which is defined relative to the yield strain. The factor of safety is calculated as the yield strain divided by the peak cladding strain. A factor of safety greater than unity indicates that the cladding remains below yield, whereas a value less than unity is indicative of plastic deformation. In all cases of this study a safety factor over 1.0 was calculated, although in the most limiting case at 300°C the safety factor was only 1.01, which suggests that yielding could occur when additional loads like rod internal pressure are included. When the temperature is restricted to 200°C the limiting safety factor increases to 1.28, which has significant margin to accommodate internal pressure and potential local cladding defects that could cause a local stress concentration. An important trend in the calculated fuel rod mechanical loads is that the 2 nd highest loaded fuel rod in an assembly tends to be significantly lower than the highest loaded rod. The implication is that even if one rod in an assembly experiences a failure the loads would have to be significantly higher to cause two or more rods to fail.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

An Overview of the Patch Integral Method (PIM), a New Heat Transfer Analysis Tool for Hypersonic Wind Tunnel Facilities at NASA Langley

NASA Langley’s hypersonic wind tunnels are heavily leveraged for planetary missions. The data collection method in these tunnels is thermography, and surface temperature measurements of the model surface are collected and reduced to produce surface heating data, as seen in Fig 1. However, during model injection, no temperature data are collected, and thus conventional, integral heat transfer methods cannot be used to solve for surface heating. A method was developed in the 1990’s to reduce this data despite the data gap, known as the step approximation method. The method assumes that the film coefficient behaves as a step function, the model is semi-infinite, and thermal properties are constant. With these simplifying assumptions, a Laplace transform can be performed to result in an equation that takes the initial temperature of the model and a temperature at some point in time to back out the film coefficient at that time. This is the method that is used in the current thermographic data reduction software, IHEAT. While computationally light-weight, the step approximation has several issues associated with it. The time-history of temperature is not accounted for, which is vital as heat transfer is an integral process. Additionally, the required semi-infinite assumption is unnecessary and might be violated during runtime. Thermal variation of material properties can have a sizeable impact on heating results and are not modeled by the method. This method also takes multiple seconds to “collapse” to a steady state, which is undesirable from both a facility and data reduction standpoint. The method is also very sensitive to the “effective time” approximation, an approximation of when heating instantaneously starts (which is a nonphysical simplification), and a small variation in this value can result in an error in heating results.

J. S. Cheatwood↗

Overcoming persistent challenges in putting environmental flow policy into practice: a systematic review and bibliometric analysis

The implementation of environmental flows (e-flows) aims to reduce the negative impacts of hydrological alteration on freshwater ecosystems. Despite the growing attention to the importance of e-flows since the 1970s, actual implementation has lagged. Therefore, we explore the limitations in e-flows implementation, their systemic reasons, and solutions. We conducted a systematic review and a bibliometric analysis to identify peer-reviewed articles published on the topic of e-flows implementation research in the last two decades, resulting in 68 research and review papers. Co-occurrence of terms, and geographic and temporal trends were analyzed to identify the gaps in environmental water management and propose recommendations to address limitations on e-flows implementation. We identify the underlying causes and potential solutions to such challenges in environmental water management. The limitations to e-flow implementation identified were categorized into 21 classes. The most recognized limitation was the competing priorities of human uses of water (n = 29). Many secondary limitations, generally co-occurring in co-causation, were identified as limiting factors, especially for implementing more nuanced and sophisticated e-flows. The lack of adequate hydrological data (n = 24) and ecological data (n = 28) were among the most mentioned, and ultimately lead to difficulties in starting or continuing monitoring/adaptive management (n = 28) efforts. The lack of resource/capacity (n = 21), experimentation (n = 19), regulatory enforcement (n = 17), and differing authorities involved (n = 18) were also recurrent problems, driven by the deficiencies in the relative importance given to e-flows when facing other human priorities. In order to provide a clearer path for successful e-flow implementation, system mapping can be used as a starting point and general-purpose resource for understanding the sociohydrological problems, interactions, and inherited complexity of river systems. Secondly, we recommend a system analysis approach to address competing demands, especially with the use of coupled water-energy modeling tools to support decision-making when hydropower generation is involved. Such approaches can better assess the complex interactions among the hydrologic, ecological, socioeconomic, and engineering dimensions of water resource systems and their effective management. Lastly, given the complexities in environmental water allocation, implementation requires both scientific rigor and proven utility. Consequently, and where possible, we recommend a move from simplistic flow allocations to a more holistic approach informed by hydroecological principles. To ease conflicts between competing water demands, water managers can realize more 'pop per drop' by supporting key components of a flow regime that include functional attributes and processes that enhance biogeochemical cycling, structural habitat formation, and ecosystem maintenance.

54 ENVIRONMENTAL SCIENCES↗

Modeling of the metal–insulator transition temperature in alio-valently doped VO 2 through symbolic regression

The correlated semiconductor vanadium dioxide (VO 2 ) exhibits an insulator–metal transition (IMT) near room temperature, which is of interest in various device applications. Precise IMT temperature control is crucial to determine the use cases across technologies such as thermochromic windows, actuators for robots or neuronal oscillators. Doping the cation or anion sites can modulate the IMT by several tens of degrees and control hysteresis. However, modeling the effects of control parameters (e.g., doping concentration, type of dopants) is challenging due to complex experimental procedures and limited data, hindering the use of traditional data-driven machine learning approaches. Symbolic regression (SR) can bridge this gap by identifying nonlinear expressions connecting key input parameters to target properties, even with small data sets. In this work, we develop SR models to capture the IMT trends in VO 2 influenced by different dopant parameters. Using experimental data from the literature, our study reveals a dual nature of the IMT temperature with varying tungsten (W) doping concentrations. The symbolic model captures data trends and accounts for experimental variability, providing a complementary approach to first-principles calculations. Our feature-driven analysis across a broader class of dopants informs selectivity and provides qualitative insights into tuning phase transition properties valuable for neuromorphic computing and thermochromic windows.

36 MATERIALS SCIENCE↗

An effective QWBA/UHPLC-MS/tissue punch approach: solving a pharmacokinetic issue via quantitative Met-ID

Methods to provide absolute quantitation of the administered drug and corresponding metabolites in tissue in a spatially resolved manner is a challenging but much needed necessity in pharmaceutical research. Quantitative whole-body autoradiography (QWBA) after a single-dose intravenous (3 mg/kg) and extravascular (30 mg/kg) administrations of an in vitro metabolically stable test compound (structure not reported here) indicated quick tissue distribution and excretion. Good bioavailability and short in vivo half-lives were determined formerly for the same test compound. For closing gaps in the understanding of pharmacokinetic data and in vitro results, radioactive hot spots on whole-body tissue sections had been profiled. Punches from selected tissue regions containing high radioactivity in the tissue sections previously analyzed by QWBA were extracted by a highly organic solvent and analyzed without any consecutive sample preparation step, applying ultra high performance liquid chromatography-mass spectrometry (UHPLC-MS) and off-line radioanalysis to maximize signal levels for metabolite identification and profiling. The analysis revealed that the test compound was metabolized intensively by phase I reactions in vivo and the metabolites formed were excreted in bile and in urine. The predominant metabolites showed abundant signal intensities both by MS and by radioanalysis but the MS signal intensities generally underestimated the real abundances of metabolites relative to the unchanged drug. In this work we illustrate that maximizing the sensitivity of tissue punch radioanalysis and the combination with UHPLC-MS leads to a better insight of pharmacokinetic processes by providing quantitative data with high molecular selectivity.

60 APPLIED LIFE SCIENCES↗

Data for Application of Time-Domain 1H NMR for Investigating Dynamics of Vegetative Lipids in Bioenergy Crops at Different Developmental Stages

Sweet sorghum is typically cultivated for the food and fodder market. Recently, sweet sorghum varieties are being metabolically transitioned to enhance energy density by accumulating oil droplets in their vegetative tissues for bioenergy applications. Owing to the high biomass yield of sorghum, the transgenic lines can compete with oil-seed crops for biodiesel yield per unit area. In the initial phase of transgenic development, a high-throughput phenotyping method can bridge the gap between the production pipeline and analysis to improve the efficiency of the process. To meet the requirement, the present study extends the application of time-domain 1H-NMR spectroscopy for rapid quantification and characterization of the total in-situ lipids of sweet sorghum ‘ramada’ to lay the groundwork for analyzing the upcoming large quantity of transgenic samples. NMR technology has been successfully established for analyzing lipid contents of vegetative tissues of non-transgenic variety. The multiexponential analysis of spin-lattice (T1) relaxation spectra obtained from TD-NMR aided the investigation of the dynamics of the free and bound lipid fraction with plant development. The total lipid concentration of bagasse and leaves of non-transgenic sweet sorghum remained unchanged throughout the plant development. Leaves displayed a higher percentage of bound lipids as compared to bagasse. A significant variation in the lipid concentration of juice was observed at the different growth stages with a maximum lipid accumulation of 1.21 ± 0.04% w/w at the boot stage that decreased with further maturity of the plant.

Biomass Analytics↗

From roads to roofs: How urban and rural mobility influence building energy consumption

In this article, understanding the relationship between travel behavior and building energy use at an urban scale is crucial for developing effective energy management strategies. Mobility patterns significantly impact building occupancy, which in turn affects energy consumption. However, existing methods often focus on individual buildings, whereas geographical influences on energy usage are not adequately examined. This study addresses this gap by using transportation origin-destination (OD) data to estimate building occupancy and energy. The proposed method assigns OD trips from census block groups to the building level, incorporating building, travel survey, and census data to derive building occupancy profiles. This method was applied to urban and rural areas with 4062 buildings in 70 census block groups. We found that the OD-informed occupancy profile exhibits smoother energy consumption patterns compared with that of Department of Energy reference occupancy profiles. Our analysis reveals distinct building energy consumption patterns among groups with long and short commutes, emphasizing the effect of commute times and work schedules on residential energy usage. This framework is useful for practitioners in transportation agencies and utility companies, enabling the estimation of building energy based on mobility patterns. Overall, this study shows the potential of integrating transportation and building energy data to inform cross-sector energy management strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An analysis of the back end of the nuclear fuel cycle with emphasis on high-level waste management, volume 1

The programs and plans of the U.S. government for the "back end of the nuclear fuel cycle" were examined to determine if there were any significant technological or regulatory gaps and inconsistencies. Particular emphasis was placed on analysis of high-level nuclear waste management plans, since the permanent disposal of radioactive waste has emerged as a major factor in the public acceptance of nuclear power. The implications of various light water reactor fuel cycle options were examined including throwaway, stowaway, uranium recycle, and plutonium plus uranium recycle. The results of this study indicate that the U.S. program for high-level waste management has significant gaps and inconsistencies. Areas of greatest concern include: the adequacy of the scientific data base for geological disposal; programs for the the disposal of spent fuel rods; interagency coordination; and uncertainties in NRC regulatory requirements for disposal of both commercial and military high-level waste.

Source record↗

Multi-Disciplinary Design Optimization Using WAVE

The current preliminary design tools lack the product performance, quality and cost prediction fidelity required to design Six Sigma products. They are also frequently incompatible with the tools used in detailed design, leading to a great deal of rework and lost or discarded data in the transition from preliminary to detailed design. Thus, enhanced preliminary design tools are needed in order to produce adequate financial returns to the business. To achieve this goal, GEAE has focused on building the preliminary design system around the same geometric 3D solid model that will be used in detailed design. With this approach, the preliminary designer will no longer convert a flowpath sketch into an engine cross section but rather, automatically create 3D solid geometry for structural integrity, life, weight, cost, complexity, producibility, and maintainability assessments. Likewise, both the preliminary design and the detailed design can benefit from the use of the same preliminary part sizing routines. The design analysis tools will also be integrated with the 3D solid model to eliminate manual transfer of data between programs. GEAE has aggressively pursued the computerized control of engineering knowledge for many years. Through its study and validation of 3D CAD programs and processes, GEAE concluded that total system control was not feasible at that time. Prior CAD tools focused exclusively on detail part geometry and Knowledge Based Engineering systems concentrated on rules input and data output. A system was needed to bridge the gap between the two to capture the total system. With the introduction of WAVE Engineering from UGS, the possibilities of an engineering system control device began to formulate. GEAE decided to investigate the new WAVE functionality to accomplish this task. NASA joined GEAE in funding this validation project through Task Order No. 1. With the validation project complete, the second phase under Task Order No. 2 was established to develop an associative control structure (framework) in the UG WAVE environment enabling multi-disciplinary design of turbine propulsion systems. The capabilities of WAVE were evaluated to assess its use as a rapid optimization and productivity tool. This project also identified future WAVE product enhancements that will make the tool still more beneficial for product development.

Irwin, Keith↗

Microshutter Arrays for the NGST NIRSpec

We are developing a programmable multiobject field selector for the NGST NIRSpec. This device is a microshutter array, a close-packed 2000 x 2000 array of 100 micrometer x 100 micrometer shutters fabricated with Micro-ElectroMechanical Systems (MEMS) technologies. The shutters are opened using a magnet scanned over the array. The shutters are held open by electrostatic potentials on adjacent vertical electrodes. Modeling of the magnetic actuation of the microshutters allowed optimization of the magnetic field configuration, the distance between magnet and shutters, and the force and torque produced by the magnet. The results of laboratory tests are consistent with our modeling. We have demonstrated actuation, latching and addressing. We are able to rotate shutters out of the plane up to 90 degree and more, to latch them electrostatically to the walls and release them selectively. During the last six month all critical elements of the array have been demonstrated. Fabrication processes were developed to deposit vertical electrodes on support grid side walls and insulated light-shields that block the gaps between shutters and the support grid. Physical optics analysis was performed to assess the expected optical performance of the microshutters. A preliminary Fourier optics analysis on the microshutter array performance has been carried out. More detailed analysis of wave propagation through 3D structures is a next step. An optical test station for verifying optical parameters of the shutter array at room temperature has been developed. It allows to measure parameters, such as transmission, scattering, contrast ratio, and diffraction of the array structure. Initial data have been acquired and are being analyzed and compared to theoretical predictions.

Moseley, Harvey↗

4.2.1.31 Integrated Life Cycle Sustainability Analysis

This project provides the Department of Energy's Bioenergy Technologies Office (BETO) with strategic decision-support for the evaluation of its R&D portfolio by developing, validating, and applying a coherent methodology and consistent model framework to quantify the net effects of an expanding US bioeconomy. The framework fills an analysis gap previously identified by Peer Review and supports a related milestone in BETO's Multi-Year Program Plan. The framework was scoped with inputs from practitioners in academia, national laboratories, and federal agencies. The model is a top-down, economy-wide framework using a coherent methodology to compute environmental and socio-economic metrics. It is purposefully complementary to existing bottom-up, process-based techno-economic and life cycle assessment BETO tools and uses their data as inputs. Presently, the model covers several commercial and near-commercial biofuel routes and an emerging pathway for plastics upcycling. It covers temporal detail across four time-steps and is currently being expanded with a prospective modeling capability. The model has provided analyses for the Third Triennial Report to Congress (RtC3) on the environmental impacts of the Renewable Fuel Standard (RFS2), among others. As part of this project, NREL also provides scientific support to BETO in the International Energy Agency's Technology Collaboration Program on Bioenergy (IEA Bioenergy) Task 45 on Sustainability. Here, NREL evaluates and synthesizes activities that develop, compare, or apply metrics, methods, and tools to quantify sustainability effects of bioeconomy products. NREL also coordinates related national lab involvement and a BETO Working Group on Sustainable Land Management.

bioeconomy↗

GeoBridge: Unearthing Insights from Connecting Communities to Geothermal Information and Opportunities: Preprint

Knowledge is essential for overcoming obstacles in the development and adoption of geothermal technologies, and the geothermal community is home to numerous tools, events and organizations dedicated to sharing knowledge. However, many of these tools can be difficult to find, their resources undiscoverable by search engines, available only to members, or hidden away behind pay walls (Weers et al., 2024). The Department of Energy's (DOE) GeoBridge was developed by the National Renewable Energy Laboratory (NREL) to help bridge gaps in information and connect the geothermal community to the resources it needs. Launched in October 2024, GeoBridge aspires to expand the pool of geothermal stakeholders by providing in-roads to geothermal information, tools, and community resources. It helps to make these resources available to the broader geothermal community as well as those looking to join, such as entrepreneurs or innovators in adjacent industries looking to expand into geothermal energy. This paper explores a post-launch analysis of GeoBridge including data from analytics, feedback from GeoBridge users, the geothermal community, and the GeoBridge Advisory Group as well as an analysis of efficacy of various promotions for GeoBridge.

15 GEOTHERMAL ENERGY↗