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At least 163 records · Page 9

Embedded Sensors for Measuring Surface Regression

The development and evaluation of new hybrid and solid rocket motors requires accurate characterization of the propellant surface regression as a function of key operational parameters. These characteristics establish the propellant flow rate and are prime design drivers affecting the propulsion system geometry, size, and overall performance. There is a similar need for the development of advanced ablative materials, and the use of conventional ablatives exposed to new operational environments. The Miniature Surface Regression Sensor (MSRS) was developed to serve these applications. It is designed to be cast or embedded in the material of interest and regresses along with it. During this process, the resistance of the sensor is related to its instantaneous length, allowing the real-time thickness of the host material to be established. The time derivative of this data reveals the instantaneous surface regression rate. The MSRS could also be adapted to perform similar measurements for a variety of other host materials when it is desired to monitor thicknesses and/or regression rate for purposes of safety, operational control, or research. For example, the sensor could be used to monitor the thicknesses of brake linings or racecar tires and indicate when they need to be replaced. At the time of this reporting, over 200 of these sensors have been installed into a variety of host materials. An MSRS can be made in either of two configurations, denoted ladder and continuous (see Figure 1). A ladder MSRS includes two highly electrically conductive legs, across which narrow strips of electrically resistive material are placed at small increments of length. These strips resemble the rungs of a ladder and are electrically equivalent to many tiny resistors connected in parallel. A substrate material provides structural support for the legs and rungs. The instantaneous sensor resistance is read by an external signal conditioner via wires attached to the conductive legs on the non-eroding end of the sensor. The sensor signal can be transmitted from inside a high-pressure chamber to the ambient environment, using commercially available feedthrough connectors. Miniaturized internal recorders or wireless data transmission could also potentially be employed to eliminate the need for producing penetrations in the chamber case. The rungs are designed so that as each successive rung is eroded away, the resistance changes by an amount that yields a readily measurable signal larger than the background noise. (In addition, signal-conditioning techniques are used in processing the resistance readings to mitigate the effect of noise.) Hence, each discrete change of resistance serves to indicate the arrival of the regressing host material front at the known depth of the affected resistor rung. The average rate of regression between two adjacent resistors can be calculated simply as the distance between the resistors divided by the time interval between their resistance jumps. Advanced data reduction techniques have also been developed to establish the instantaneous surface position and regression rate when the regressing front is between rungs.

Gramer, Daniel J.↗

Analysis of H-Canyon Process Tanks in Preparation of Consolidation and Blending for HALEU Fuels

High-Assay Low- Enriched Uranium (HALEU) fuels are being developed to support the replacement of Highly Enriched Uranium (HEU) fuels used in U.S. High-Performance Research Reactors (USHPRR) as well as advanced nuclear power reactor designs. The projected demand for HALEU far exceeds the supply and studies are underway to assess various options to partially mitigate the potential short supply. The H Canyon facility at the Savannah River Site (SRS) Low Enriched Uranium (LEU) containing 4.95% U-235 from the reprocessing of highly enriched foreign and domestic research reactor fuel for the Tennessee Valley Authority’s (TVA) commercial power reactor market for several decades. The production of LEU at the H-Canyon facility can be readily transitioned to produce 19.75% HALEU solutions from the current separated inventory of purified HEU solutions in H-Canyon storage.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Chemical and physical transformations of carbon-based nanomaterials observed by liquid phase transmission electron microscopy

This article addresses recent advances in liquid phase transmission electron microscopy (LPTEM) for studying nanoscale synthetic processes of carbon-based materials that are independent of the electron beam—those driven by nonradiolytic chemical or thermal reactions. In particular, we focus on chemical/physical formations and the assembly of nanostructures composed of organic monomers/polymers, peptides/DNA, and biominerals. The synthesis of carbon-based nanomaterials generally only occurs at specific conditions, which cannot be mimicked by aqueous solution radiolysis. Carbon-based structures themselves are also acutely sensitive to the damaging effects of the irradiating beam, which make studying their synthesis using LPTEM a unique challenge that is possible when beam effects can be quantifi ed and mitigated. With new direct sensing, high frame rate cameras, and advances in liquid-cell holder designs, combined with a growing understanding of irradiation effects and proper experimental controls, microscopists have been able to make strides in observing traditionally problematic carbon-based materials under conditions where synthesis can be controlled, and imaged free from beam effects, or with beam effects quantified and accounted for. These materials systems and LPTEM experimental techniques are discussed, focusing on nonradiolytic chemical and physical transformations relevant to materials synthesis.

Parent, Lucas R.↗

Simple and Scalable Process for Nanocellulose Production from Residues and Waste (CRADA Final Report)

This project successfully developed an innovative, cost-effective, and scalable method for converting low-cost agricultural waste feedstocks into nanocellulose—a sustainable material with wide-ranging industrial applications. It addressed the critical challenges of high production costs and limited global supply, which have hindered the widespread adoption of nanocellulose in industry. Through this work, significant advancements were made in optimizing resource use, improving process efficiency, and reducing costs. Notable achievements included a 50% reduction in water usage, 30% lower chemical consumption, and 20% energy savings, all while maintaining high-quality product standards. The technical feasibility of the process was further validated at a 10L scale in collaboration with the Advanced Biofuels and Bioproducts Development Unit (ABPDU), demonstrating scalability and replicability. Key challenges in reducing nanocellulose production costs were addressed by utilizing low-cost biomass feedstocks and implementing low-temperature conversion reactions, leading to lower capital and operating expenses. The project also mitigated financial risk by generating critical data on the feasibility, adaptability, and scalability of the conversion technology, paving the way for its commercial implementation. Public benefits include advancing the circular bioeconomy, reducing environmental impact, fostering job creation, and enabling a shift toward biobased materials as sustainable alternatives to fossil-based products. These outcomes align closely with national goals to reduce greenhouse gas emissions and promote sustainable technological innovation.

09 BIOMASS FUELS↗

Divertor Plasma Detachment Control Neural Network

DivControlNN is a state-of-the-art software tool that leverages advanced machine learning techniques to predict and control divertor plasma behavior in fusion reactors. Plasma, a highly energetic and electrically charged gas, requires meticulous management to protect reactor components and maintain optimal energy production. Conventional simulation methods, although extremely detailed, typically demand extensive computational time-making them unsuitable for real-time control scenarios. DivControlNN addresses this challenge by learning from tens of thousands of high-fidelity simulations, thereby creating a rapid surrogate model that can deliver near-instantaneous predictions. At the core of its functionality is a sophisticated technique known as latent space mapping, which condenses complex, high-dimensional plasma data into a compact, lower-dimensional representation. This streamlined representation enables the system to quickly forecast essential plasma properties and determine the precise conditions required for effective detachment. Detachment is a crucial process in which the plasma is cooled before reaching the divertor plates, thereby reducing heat loads and mitigating material erosion. In recent experiments conducted on the KSTAR tokamak in South Korea, DivControlNN successfully guided the detachment process without any fine-tuning-even when applied to a new tungsten divertor configuration. By achieving a computational speed-up of over one hundred million times compared to traditional simulation methods while maintaining low prediction errors, DivControlNN stands to significantly enhance real-time control and diagnostic capabilities in future fusion reactors. This breakthrough paves the way for safer, more reliable reactor operation and represents a major advancement toward realizing fusion energy as a practical, sustainable, and clean power source.

Xu, Xueqiao [Lawrence Livermore National Laborator↗

Nanostructured Alumina Forming Austenitic Alloy (NAFA) Production using Advanced Manufacturing

Alumina-forming austenitic (AFA) alloys are well known for their exceptional corrosion-resistant properties due to the formation of a dense oxide scale beneficial in their application as a nuclear material. However, use of the alloys in core material applications is limited due to the high nickel-transmutation and helium generation rate in service, leading to swelling and reduced lifetimes. Enhancing the sink strength to pin gas bubbles and increasing gas management of the material may mitigate many of the degradation phenomena expected during alloy deployment (such as high-temperature helium embrittlement and cavity swelling for lead-cooled fast-reactor applications). Nanostructured materials are usually produced using a time-consuming and expensive batch process like mechanical alloying to achieve the fine homogenous distribution of nanoprecipitates throughout the matrix material. Integrating the nanoprecipitates in modern additive manufacturing processes has proven difficult, as the required nano-sizes or number densities cannot be achieved simultaneously. Efforts to increase the number density of precipitates by adding more precipitate-forming rare-earth elements led to agglomeration of such elements, while the nano-sized precipitates did not form in sufficient quantity when not enough rare-earth element was use. In this work a novel approach to advanced manufacturing and the fabrication of Nanostructured AFA (NAFA) materials was chosen. A dual precipitate-forming NAFA steel with a chemistry more suitable for advanced reactor applications was produced to create an environmentally resistant, high-sink-strength austenitic alloy for advanced reactor cladding applications.

36 MATERIALS SCIENCE↗

Nanostructured Alumina-Forming Austenitic Alloy (NAFA) Production Using Advanced Manufacturing

Alumina-forming austenitic (AFA) alloys are well known for their exceptional corrosion-resistant properties due to the formation of a dense oxide scale beneficial in their application as a nuclear material. However, use of the alloys in core material applications is limited due to the high nickel-transmutation and helium generation rate in service, leading to swelling and reduced lifetimes. Enhancing the sink strength to pin gas bubbles and increasing gas management of the material may mitigate many of the degradation phenomena expected during alloy deployment (such as high-temperature helium embrittlement and cavity swelling for lead-cooled fast-reactor applications). Nanostructured materials are usually produced using a time-consuming and expensive batch process like mechanical alloying to achieve the fine homogenous distribution of nanoprecipitates throughout the matrix material. Integrating the nanoprecipitates in modern additive manufacturing processes has proven difficult, as the required nano-sizes or number densities cannot be achieved simultaneously. Efforts to increase the number density of precipitates by adding more precipitate-forming rare-earth elements led to agglomeration of such elements, while the nano-sized precipitates did not form in sufficient quantity when not enough rare-earth element was use. In this work a novel approach to advanced manufacturing and the fabrication of Nanostructured AFA (NAFA) materials was chosen. A dual precipitate-forming NAFA steel with a chemistry more suitable for advanced reactor applications was produced to create an environmentally resistant, high-sink-strength austenitic alloy for advanced reactor cladding applications.

36 MATERIALS SCIENCE↗

Biotransformation of Pesticides across Biological Systems: Molecular Mechanisms, Omics Insights, and Biotechnological Advances for Environmental Sustainability

The widespread application of pesticides such as organophosphates, organochlorides, and triazines in modern agriculture has led to their notable presence in soils, water bodies, and food chains, raising concerns about persistence, bioaccumulation, and adverse effects on nontarget organisms. Biotransformation, the enzymatic transformation of xenobiotic compounds by microorganisms, plants, and animals, plays a pivotal role in the degradation and detoxification of these chemicals. This review provides a comprehensive examination of the mechanisms, key enzyme classes (e.g., hydrolases, oxidoreductases, transferases), and environmental factors influencing pesticide biotransformation across different biological systems. Recent advances in omics technologies have revolutionized the understanding of microbial and plant metabolism, while synthetic biology offers opportunities for engineering enhanced degradation capabilities. The environmental fate of transformation products is also discussed, together with a critical analysis of challenges, unresolved questions, and future research directions, offering a holistic perspective on pesticide biotransformation as a key process for mitigating chemical pollution.

Biotransformation↗

Enhanced Modeling of GHG Emissions and Mitigation in NEMS Component Design Report

The Office of Fossil Energy and Carbon Management (FECM), together with OnLocation, has developed a custom version of the National Energy Modeling System (NEMS), “FECM-NEMS”, that includes additional representation of energy- and industry-sector GHG emissions and mitigation options beyond those represented in the U.S. EIA's NEMS. Compared with GHG emissions published by the EPA in their Inventory of U.S. GHG Emissions and Sinks: 1990-2021, FECM-NEMS endogenously represents 81% of gross U.S. GHG emissions; however, the remaining 19%, as well as LULUCF-sector emissions and removals, are still required to properly model net-zero GHG scenarios, which requires an accounting of all GHGs. Considering recent technological advances to mitigate CO 2 and non-CO 2 emissions, the Office of Carbon Management (OCM) within FECM had tasked OnLocation with creating this component design report (CDR) to address the gap in GHG representation. This report describes how FECM-NEMS could incorporate missing GHG emissions (including LULUCF-sector emissions and removals) and engineered processes for GHG mitigation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Materials Challenges in Space Exploration

United States civil space program administered by National Aeronautics and Space Administration (NASA) has a new strategic direction to explore the solar system. This new 'vision for space exploration' encompasses a broad range of human and robotic missions, including the Moon, Mars and destinations beyond. These missions require advanced systems and capabilities that will accelerate the development of many critical technologies, including advanced materials and structural concepts. Specifically, it is planned to develop high-peformance materials for vehicle structures, propulsion systems, and space suits; structural concepts for modular assembly for space infrastructure; lightweight deployable and inflatable structures for large space systems and crew habitats; and highly integrated structural systems and advanced thermal management systems for reducing launch mass and volume. This paper will present several materials challenges in advanced space systems-high performance structural and thermal materials, space durable materials, radiation protection materials, and nano- structural materials. The paper will also address smart materials and structures and examine space environmental effects on materials and methods of mitigating them. Finally, the paper will take a look at the possibility of utilizing materials in situ, i.e., processing and using desired materials on the surface of the Moon and Mars.

Bhat, Biliyar N.↗

Advanced Autonomous Welding for Refabrication and Follow-On Testing of Previously Irradiated Nuclear Fuel

The performance of follow-on experiments using irradiated nuclear fuel at any point in its lifecycle is a critical step in understanding phenomena and behavior. Transient experiments with high-burnup fuel can deepen the understanding of fuel fragmentation, relocations, and dispersal under loss-of-coolant accidents. An advanced autonomous welding process to refabricate commercial fuel rods inside a hot cell was created and tested to enable flexible experiment approaches on fuels irradiated in commercial and test reactors. Irradiated light water reactor fuel test pins from experiments performed at the Advanced Test Reactor (ATR) at Idaho National Laboratory were used to demonstrate the refabrication process. The welding process was found to be sensitive to welding parameters but flexible such that multiple passes could be performed on the same location until a hermetic weld was obtained. The refabrication of rodlets and successful welds was also found to be sensitive to the preparation of the irradiated cladding and endcaps. Thorough defueling of the fuel at the weld location and proper sizing of the endcaps and backing material mitigated these issues. The use of strategically located heat sinks in contact with the cladding and endcap materials also increased welding and refabrication success. For this work, the test pins were sectioned to remove the original endcaps and fuel was removed from both ends of each rodlet. The reassembly of the rodlets was then completed in four steps, which included the press fitting of new endcaps, the circumferential welding of rodlet endcaps to the cladding, rodlet pressurization in a pressure chamber, and seal welding the rodlet under pressure. The integrity of the refabricated rodlets was then verified via helium leak checking inside a vacuum chamber. The advanced welding system is capable of refabricating rodlets up to 380 mm in length, and repressurizing them up to 15 500 kPa. The refabricated lengths of the rodlets used in this work ranged from 149 to 165 mm and the refabricated fuel stack heights ranged from 70.4 to 79.8 mm. Here, the rodlets were pressurized with argon to an average pressure of 3617 kPa, and the average leak rate after refabrication was 6.7 • 10 -8 cm 3 • s -1 .

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Haze Mitigation in High-Resolution Satellite Imagery using Enhanced Style-Transfer Neural Network and Normalization Across Multiple GPUs

Despite recent advances in deep learning approaches, haze mitigation in large satellite images is still a challenging problem. Due to amorphous nature of haze, object detection or image segmentation approaches are not applicable. Also it is practically infeasible to obtain ground truths for training. Bounded memory capacity of GPUs is another constraint that limits the size of image to be processed. In this paper, we propose a style transfer based neural network approach to mitigate haze in a large overhead imagery. The network is trained without paired ground truths; further, perception loss is added to restore vivid colors, enhance contrast and minimize artifacts. The paper also illustrates our use of multiple GPUs in a collective way to produce a single coherent clear image where each GPU dehazes different portions of a large hazy image.

Park, Byung↗

Comprehensive defect evaluation of advanced nuclear fuels using high-resolution acoustic signals and optimized sensor separation

Graphite pebble composite structures based on TRistructural-ISOtropic (TRISO) particles are being developed as core nuclear fuels in advanced power reactors, promising safe operation at increased temperatures. Ensuring the structural integrity of these nuclear fuels requires comprehensive and accurate non-destructive evaluation (NDE) techniques to characterize defects and damage in the pebbles. However, traditional acoustic evaluation methods face limitations in defect characterization due to the highly attenuative, and geometrically and compositionally complex nature of these structures. This study proposes an improved acoustic NDE technique for accurate detection and classification of anticipated relevant defects and damage in graphite pebbles using high-resolution acoustic signals and optimized transmit-receive sensor networks. The proposed approach utilizes a triangular three-sensor network as the base unit, comprising three transmit-receive sensors. The sensor separation distance, as well as acoustic excitation center frequency, pulse-width, and bandwidth are optimized to enhance spatial resolution and improve signal-to-noise ratio, enabling effective characterization of the smallest size and widest range of defects in pebbles. Furthermore, the use of the triangular sensor configuration instead of a more conventional transmit-receive sensor pair expands the inspection region from a one-dimensional linear path to a two-dimensional area, increasing spatial coverage. To mitigate challenges associated with processing of complex acoustic signals arising from high-frequency, high-bandwidth excitation in these structures, a machine-learning-based signal processing algorithm is integrated with the sensor network. In the machine-learning-based algorithm, multi-domain features are extracted from the acoustic signals to capture intricate signal characteristics, significantly improving defect identification and classification compared to traditional approaches. The proposed acoustic NDE technique offers considerable promise for practical and reliable defect/damage diagnostics of advanced nuclear pebble fuels.

42 ENGINEERING↗

Proton Selective Nanoporous Atomically Thin Graphene Membranes for Vanadium Redox Flow Batteries

Angstrom-scale proton-selective pores in atomically thin 2D materials present fundamentally new opportunities for advancing proton exchange membranes (PEMs). Vanadium Redox Flow Batteries (VRFBs) for grid-scale energy storage require PEMs with high areal proton conductance (>1 S cm −2 ) and minimal vanadium ion (VO 2+ ) crossover. However, state-of-the-art Nafion 212 membranes (N212 ≈50 µm thick), suffer from persistent VO 2+ crossover reducing performance and efficiency. Here, a layered PEM is demonstrated, comprising monolayer CVD graphene with Angstrom-scale proton-selective pores introduced via Ar plasma, integrated with an ultra-thin ≈300 nm polybenzimidazole (PBI) layer and sandwiched between two Nafion 211 (25 µm thick) layers. The layered architecture facilitates scalable membrane fabrication by mitigating defects while processing and facile stacking of graphene layers allows stochastic non-selective defect isolation enabling exceptionally low VO 2+ crossover (selectivity (H + areal conductance / VO 2+ permeability) ≈6709 × 10 6 S min cm −4 ), with proton conductance >8 S cm −2 . Systematic transport experiments supported by resistance-based transport modelling elucidate the role of defect size, defect isolation, and sealing, as well as layering/stacking, to enable orders of magnitude (>671× over N212) improvements in selectivity, along with areal proton conductance >8 S cm −2 . This work highlights the potential of atomic-scale proton-selective defect engineering in 2D materials, in conjunction with facile stacking and layering of materials as strategies for scalable, high-performance advances in PEMs for energy, electrochemical, and separation applications beyond VRFBs.

Chaturvedi, Pavan [Vanderbilt Univ., Nashville, TN↗

Capability Building Progression of an Insider Threat Mitigation Program at an International Research Reactor

The nuclear industry recognizes the difficulties involved in developing effective managerial and leadership skills in a highly technical and proficient workforce such as that found in nuclear facilities. Implementing an insider threat mitigation program (ITMP) within the nuclear industry is a complex and ongoing process that demands a comprehensive understanding of human behavior, an organization’s security culture, and rigorous regulatory requirements yet also accounts for facility characteristics, physical security, material flow, and activities involving nuclear material. Given the high-consequence nature of research reactor operations, even minor lapses can lead to safety, security, and reputational risks. An effective ITMP requires a defense-in-depth approach that incorporates behavioral analysis, robust vetting procedures, continuous monitoring, and cross-disciplinary coordination. It must also promote a culture of vigilance and accountability at all levels up to and including executive leadership but be flexible enough to adapt to evolving global threats and technological advances. Insider threat mitigation is not a one-time effort but rather a sustained commitment to excellence in safety and security. Establishing a culture in which personnel proactively report incidents and issues that could affect nuclear safety and security is vital to maintaining a safe and secure operational environment. This document was developed to guide senior management and research reactor organizations in creating comprehensive programs to effectively manage and mitigate insider threat behaviors and actions. It focuses on the key pillars of an effective ITMP, including the national legal framework, security culture, preventive and protective measures, cyber security, and performance evaluation. By using a systematic approach during implementation, facilities can foster environments conducive to insider threat detection and support long-term program sustainability. The document also provides strategies for improving communication across all levels of an organization, helping to eliminate barriers that hinder the development of robust ITMPs and enhance overall security culture. In today’s organizations, the concept of leveraging safety and security culture lessons to facilitate knowledge transfer is rapidly evolving to expedite insider threat management and security culture improvements. This document outlines the rationale for evaluating an ITMP based on national customs, culture, and stakeholders. The elements are all germane to reliability and trustworthiness and relate to security concerns that states may encounter. The document focuses not only on individual perceptions regarding security issues and capability building but also on team building and how to resolve concerns. The implementers of a facility’s ITMP may zero in on indicators of insider threats within their enterprise. This material will benefit organizations when it is applied using a systematic and structured approach as demonstrated throughout the document.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Biomass Gasification for Chemicals Production Using Chemical Looping Techniques (Final Report)

The Ohio State University (OSU) is investigating the Biomass to Syngas (BTS) chemical looping technology to produce syngas for chemical production applications from biomass under US Department of Energy (DOE) Award #DE-EE0007530. The BTS process aligns with the programmatic area of interest of “Conversion, via biological, thermal, catalytic or chemical means, of acceptable feedstocks into advanced biofuels and/or biobased products including intermediate and end-use products”. Compared to conventional biomass gasification processes, the BTS process eliminates the need for air separation units and tar reforming reactors, which leads to energy efficiency improvement and capital cost reduction. The overall objective is to ascertain the potential of biomass gasification based on the chemical looping technique through mitigation of the possible techno-economic challenges in the steps of scale up for commercialization. The scope of work consists of 1) designing, constructing and operating a 10 kWth commercially scalable sub-pilot BTS system and; 2) completing a comprehensive techno-economic analysis (TEA) of the BTS process using methanol production as an example. Over the course of the project, the project team completed the design, fabrication, and operation of a 10 kWth sub-pilot scale test unit for the BTS process. Corn cob and wood pellets were successfully tested in the unit for high purity syngas generation in extended test campaigns that totals over 200 hours. Syngas purity (H2 and CO) of >70% was achieved with a CH 4 concentration of <6%. The H 2 /CO ratio was greater than 1.8. A comprehensive techno-economic analysis was performed to compare the BTS process and a reference indirectly heated gasification process for methanol synthesis. The result, updated with experimental results for BTS process performance, shows a methanol required selling price (MSP) of $\$ $1.15/gal, compared to $1.28/gal for the reference case.

08 HYDROGEN↗

An Efficient Storage-Driven Machine Learning Model for Performance in the Era of Multimodal Scientific Data

Scientific workflows are increasingly relying on machine learning (ML), simulation, and hybrid techniques to predict, understand, and optimize the behavior of complex experiments. High-performance computing has greatly improved researchers’ ability to acquire diverse data modalities in these workflows. Recent studies suggest that the performance of machine learning models can be improved by integrating data from various sources. Unfortunately, these workloads pose unprecedent pressure on the network storage to meet the demands associated with accessing these multimodal data. To mitigate the impact of intensive IO, we propose a solution that utilizes a multi-tier High-Performance Computing (HPC) distributed storage and data processing framework, placing computation where the data resides for better performance. By adopting this project, the scientific community will gain new opportunities to explore multimodal storage-driven possibilities, integrating multiple scientific data sources with advanced streaming frameworks. Additionally, our framework effectively utilizes computing resources and bridges the gaps identified by HPC experts. Our proposed approach tackles scalability and persistence challenges by leveraging native persistency, which has posed difficulties in traditional approaches. Furthermore, we seek to enhance fault-tolerance and load-balance of computations by leveraging real-time streaming in diverse scientific computing environments, thereby propelling advanced scientific computing research into the next generation.

97 MATHEMATICS AND COMPUTING↗

ExMC Technology Watch

The Technology Watch (Tech Watch) project is directed by the NASA Human Research Programs (HRP) Exploration Medical Capability (ExMC) element, and primarily focuses on ExMC technology gaps. The project coordinates the efforts of multiple NASA centers, including the Johnson Space Center (JSC), Glenn Research Center (GRC), Ames Research Center (ARC), and the Langley Research Center (LaRC). The objective of Tech Watch is to identify emerging, high-impact technologies that augment current NASA HRP technology development efforts. Identifying such technologies accelerates the development of medical care and research capabilities for the mitigation of potential health issues encountered during human space exploration missions. The aim of this process is to leverage technologies developed by academia, industry and other government agencies and to identify the effective utilization of NASA resources to maximize the HRP return on investment. The establishment of collaborations with these entities is beneficial to technology development, assessment and/or insertion, and advance NASAs goal to provide a safe and healthy environment for human exploration. In fiscal year 2013, the Tech Watch project maintained student project activity aimed at specific ExMC gaps, completed the gap report review cycle for all gaps through a maturated gap report review process, and revised the ExMC Tech Watch Sharepoint site for enhanced data content and organization. Through site visits, internships and promotions via aerospace journals, several student projects were initiated and completed this past year. Upon project completion, the students presented their results via telecom or WebEx to the ExMC Element as a whole. The upcoming year will continue to forge strategic alliances and student projects in the interest of technology and knowledge gap closure. Through the population of Sharepoint with technologies assessed by the gap owners, the database expansion will develop a more comprehensive technology set for each gap. By placing such data in Sharepoint, the gap report updates in fiscal year 2014 are anticipated to be streamlined since the evaluated technologies will be readily available to the gap owners in a sortable archive, and may be simply exported into the final gap report presentation.

Technology gaps↗