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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4

NASA Electronic Parts and Packaging (NEPP) Program - Resources for SmallSats on EEE Parts

From the outside looking in, the NEPP program supports NASA's traditional approach to providing electrical, electronic, and electromechanical (EEE) assurance for space missions. Standards (military and commercial) for EEE parts are based on risk averse methodologies, drive higher costs and schedules, and, in general, provide devices that significantly lag behind commercial devices in performance aspects (speed, power efficiency, etc...). This is NOT the model most small missions realistically can use. However, when you look behind the curtain, NEPP has been considering the risk trade space for small missions for over five years and has consistently provided resources that the small mission regime would find useful. In this paper, we provide a brief overview of these resources as well as NEPP's current research/development efforts that are relevant. While we'll primarily discuss radiation assurance related issues such as data availability and usage, assurances processes for not only the radiation effects side, but also the EEE parts reliability will be touched upon.

Parts assurance↗

A Probabilistic Methodology for Determining Collision Risk of Marine Animals with Tidal Energy Turbines

Commercial development of tidal stream energy is hampered by technical and financial challenges, and impeded by uncertainty about potential environmental effects that drive environmental risk assessments and permitting (consenting) processes. The effect of greatest concern for operational tidal stream energy devices is the potential for marine animals to collide with turbine blades, resulting in injury or death. Due to the turbulent and often turbid waters that frequently characterize tidal turbine sites, there is an absence of empirical evidence about collisions with marine animals. This paucity of observations often leads to risk-averse permitting decisions that further restrict the deployment of tidal energy devices that are needed to collect this evidence. This paper relies on the framework of stressors and receptors that is widely used in marine energy studies and outlines a stepwise probabilistic methodology that applies existing knowledge to further elucidate the risk to marine animals from operational tidal turbines. A case study using striped bass from the Bay of Fundy, Canada, accompanies the methodology, to partially demonstrate its application.

16 TIDAL AND WAVE POWER↗

22 N HPGP Thruster Life Testing

In the ever-changing paradigm of efficient and capable spacecraft design, scientific missions continue pushing the envelope enabling spacecraft subsystems to deliver effective solutions to meet challenging new mission/spacecraft needs. From an in-space storable liquid chemical propulsion perspective, monopropellant hydrazine has been, and continues to be, a dependable propellant with considerable flight heritage, a variety of engine thrust classes available from multiple vendors, with repeatable and reliable performance. Additionally, the space propulsion industry has learned to successfully handle hydrazine, its regulations, the safety protocols, the personnel protective equipment, and the unique training standards–all requisite for loading spacecraft propulsion systems with toxic hypergolic hydrazine. The question now arises as to “what is next for in-space chemical propulsion?” Further, with the evolution and concrete advancements in innovative in-space green propellant technologies, capable of providing realizable benefits to scientific missions, concern over the reliability and availability of this higher performing and safer to handle class of propellants is waning. As science missions move forward with the potential flight in fusion of High Performance Green Propulsion (HPGP), NASA and its industry partners are working to address any gaps in system reliability, performance, or unique operational considerations. Propellant technology that offers both higher performance and significant reduction in personnel hazards compared to hydrazine presents an attractive propulsion subsystem design opportunity. Increased propulsion subsystem performance can result in lower spacecraft launch mass, larger scientific payloads, or extended on-orbit lifetimes. Mission trades using green propulsion technologies have been documented on multiple NASA Goddard Space Flight Center (GSFC) mission classes, examining various parameters and requirements to support mission architectures in Low Earth Orbit (LEO), High Earth Orbit (HEO), geostationary, lunar, planetary, and Quasi-halo orbit around Sun-Earth Lagrange point (L2). The results of these trade studies show promising, attainable benefits. The perceived programmatic risk of flying a newer propulsion technology has, unfortunately, not outweighed the benefits to date. To take advantage of the improved performance and mitigate programmatic risk, HPGP engines must demonstrate life testing at higher propellant throughputs than have currently been demonstrated. In an effort to proactively address the challenges with technology infusion into a risk-averse community, NASA and the Swedish National Space Agency (SNSA) outlined a collaborative Implementing Arrangement (IA) for the respective agencies to pursue increased HPGP technology maturation. This initial IA effort began in 2013, fresh off the heels of the successful PRISMA HPGP technology demonstration mission. The IA targeted objective is to reduce risk to potential future HPGP missions and fully characterize the LMP-103S propellant and associated engine performance. Over the past eight years, HPGP has flown in propulsion systems on twenty-five(25) spacecraft from seven(7) different Launch Ranges around the globe and on seven (7) different Launch Vehicles. Six(6) of these launches involved multiple loading operations for multiple spacecraft. For U.S. Range operations, nine (9) HPGP systems have been processed at Vandenberg Space Force Base(VSFB):six(6) in 2017, and three (3) in 2018. Six (6) more have been processed at Cape Canaveral Air Force Station (CCAFS)in May 2020, with three (3) systems launched in June 2020 and the remaining three (3) system were left loaded and ready until their launch in August of 2020. Three (3) more systems have been processed at Wallops Flight Facility(WFF)and launched in June 2021. In addition, these propulsion subsystems employed heritage propulsion subsystem component such as valves, filters, and pressure transducers, and have further demonstrated nominal functionality in both diaphragm and Propellant Management Device (PDM) propellant tanks. Based on these successes, HPGP technology continues to be considered for NASA Science Mission Directorate missions at GSFC. The work presented herein represents many years of development and collaborative efforts to successfully align higher performance, low toxicity hydrazine alternatives into scientific missions. NASA GSFC Propulsion Engineering, in collaboration with Bradford ECAPS, has developed mission specific thruster design and testing requirements to establish GSFC’s desired test conditions and firing sequences.In2017, the first flight-like 22N HPGP thruster Engineering Qualification Model (EQM-1)was designed and built by Bradford ECAPS to prove out the thruster design, materials, build process, and test campaign with respect to NASA GSFC critical component and mission requirements. This test program was developed to comprehensively test the thruster, the technology, and ultimately increase the 22N HPGP Technology Readiness Level(TRL). EQM-1was tested to environmental qualification levels prior to hot fire performance testing to represent the relevant end-to-end environment (launch to on-orbit operation)with required margin. This thruster demonstrated steady-state and pulse mode operational capability with propellant thruster throughput up to~53kg.At this throughput level, the EQM-1 engine began to present off-nominal performance and the test campaign was halted to allow for non-destructive testing and identify the root cause for the an omalous performance. Capitalizing on the successful elements of the EQM-1 campaign, an upgraded 22N HPGP EQM-2 has been manufactured by Bradford ECAPS to meet the complete GSFC requirements. The EQM-2 thruster’s test campaign has further demonstrated the robustness of the HPGP propulsion technology and increased the Technology Readiness Level (TRL) by undergoing a full acceptance test program, then proceeding into qualification, including environmental testing (vibration and shock to qualification levels),as well as hot-fire life testing, operating at steady-state and pulse modes with increased propellant thruster throughput to~150kg. The HPGP thruster performance testing enables effective HPGP thruster readiness evaluation to meet NASA candidate mission requirements in the future.

High↗

Demonstration of Rapid Development Through Containerization: OSE-SAT

Modern advancements in spacecraft technology have enabled engineers to develop radically smaller and lighter spacecraft, which has drastically reduced the cost of putting spacecraft into space. Despite these advancements and the shrinking cost to get spacecraft into space, space exploration is still prohibitively expensive. So much so that many space missions prefer to err on the side of caution than take on additional risk by trying newer, unproven technologies. This risk-averse mission design, while very reasonable from a program management point of view, significantly impacts engineers’ ability to solve newer, more complicated problems and limits scientists’ ability to develop more complex experiments that rely on newer technology. Often these new technologies remain stuck at lower technology readiness levels for many years due to the space community's reluctance to take on the additional risks of proving out unproven technology. The Distributed Spacecraft Autonomy (DSA) team at NASA Ames Research Center is developing a containerized solution to enable the rapid development of newer space technologies and accelerate their adoption into space missions. The Opportunistic Software Experiments for Spacecraft Autonomy Testbeds (OSE-SAT) is an on-orbit test bed that aims to reduce the amount of risk associated with newer, unproven space technologies by containerizing each experiment in its own isolated environment and providing a safe, robust, and controlled interface to access spacecraft host resources that is monitored in real time by thoroughly tested Trusted Container developed by DSA. This paper will describe DSA’s implementation of OSE-SAT and discuss the benefits, as well as challenges, of on-orbit containerization.

Aaron J Woodard↗

Space ROS TOFU: Flying Space ROS with Containerized Hybrid Trust

Space ROS is a distribution of Robot Operating System 2 (ROS2) targeting the specific requirements of flight software and spaceborne robotics while maintaining the flexibility that has made ROS indispensible for robotics research and industrial system integration. With Space ROS, a project can leverage the existing ROS2 ecosystem to reduce redundant development while tackling increasingly complex demands for on-device intelligence; however, there is no substitute for flight heritage to combat the risk-aversion common to spaceflight projects, and Space ROS has yet to fly. To break the collective-action standoff and gain valuable flight experience, the Distributed Spacecraft Autonomy (DSA) team at NASA Ames Research Center developed Opportunistic Software Experiments for Spacecraft Autonomy Testbeds (OSE-SAT) architecture, utilizing containerization to execute lower-trust software under traditionally verified heritage flight software for demonstration on-orbit. OSE-SAT leverages a hybrid-trust model where flexible, complex components like Space ROS can run without risk to the host spacecraft while providing validated feedback to a highly scrutinized, trusted core. We leverage this testbed to demonstrate Space ROS in flight, building heritage, and experience for projects with "Trust On First Use" (TOFU) requirements for flight heritage. We present a Space ROS component for OSE-SAT, lessons learned integrating Space ROS into a flight software stack, and the results of the first known use of Space ROS in orbit.

small satellites↗

Binary Quantum Control Optimization with Uncertain Hamiltonians

Optimizing the controls of quantum systems plays a crucial role in advancing quantum technologies. The time-varying noises in quantum systems and the widespread use of inhomogeneous quantum ensembles raise the need for high-quality quantum controls under uncertainties. In this paper, we consider a stochastic discrete optimization formulation of a discretized binary optimal quantum control problem involving Hamiltonians with predictable uncertainties. We propose a sample-based reformulation that optimizes both risk-neutral and risk-averse measurements of control policies, and solve these with two gradient-based algorithms using sum-up-rounding approaches. Furthermore, we discuss the differentiability of the objective function and prove upper bounds of the gaps between the optimal solutions to binary control problems and their continuous relaxations. We conduct numerical simulations on various sized problem instances based on two applications of quantum pulse optimization; we evaluate different strategies to mitigate the impact of uncertainties in quantum systems. In conclusion, we demonstrate that the controls of our stochastic optimization model achieve significantly higher quality and robustness compared with the controls of a deterministic model.

conditional value-at-risk (CVaR)↗

Multistage distributionally robust mixed-integer programming with decision-dependent moment-based ambiguity sets

We study multistage distributionally robust mixed-integer programs under endogenous uncertainty, where the probability distribution of stage-wise uncertainty depends on the decisions made in previous stages. We first consider two ambiguity sets defined by decision-dependent bounds on the first and second moments of uncertain parameters and by mean and covariance matrix that exactly match decision-dependent empirical ones, respectively. For both sets, we show that the subproblem in each stage can be recast as a mixed-integer linear program (MILP). Moreover, we extend the general moment-based ambiguity set in to the multistage decision-dependent setting, and derive mixed-integer semidefinite programming (MISDP) reformulations of stage-wise subproblems. We develop methods for attaining lower and upper bounds of the optimal objective value of the multistage MISDPs, and approximate them using a series of MILPs. We deploy the Stochastic Dual Dynamic integer Programming (SDDiP) method for solving the problem under the three ambiguity sets with risk-neutral or risk-averse objective functions, and conduct numerical studies on multistage facility-location instances having diverse sizes under different parameter and uncertainty settings. Furthermore, our results show that the SDDiP quickly finds optimal solutions for moderate-sized instances under the first two ambiguity sets, and also finds good approximate bounds for the multistage MISDPs derived under the third ambiguity set. We also demonstrate the efficacy of incorporating decision-dependent distributional ambiguity in multistage decision-making processes.

97 MATHEMATICS AND COMPUTING↗

Incorporate day-ahead robustness and real-time incentives for electricity market design

In this paper, we propose a two-stage electricity market framework to explore the participation of distributed energy resources (DERs) in a day-ahead (DA) market and a real-time (RT) market. The objective is to determine the optimal bidding strategies of the aggregated DERs in the DA market and generate online incentive signals for DER-owners to optimize the social-welfare taking into account network operational constraints. Distributionally robust optimization is used to explicitly incorporate data-based statistical information of renewable forecasts into the supply/demand decisions in the DA market. We evaluate the conservativeness of bidding strategies distinguished by different risk aversion settings. In the RT market, a bi-level time-varying optimization problem is proposed to design the online incentive signals to tradeoff the RT imbalance penalty for distribution system operators (DSOs) and the costs of individual DER-owners. This enables tracking their optimal dispatch to provide fast balancing services, in the presence of time-varying network states while satisfying the voltage regulation requirement. Simulation results on both DA wholesale market and RT balancing market demonstrate the necessity of this two-stage design, and its robustness to uncertainties, the performance of convergence, the tracking ability and the feasibility of the resulting network operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The interaction of wholesale electricity market structures under futures with decarbonization policy goals: A complexity conundrum

Competitive wholesale electricity markets can help facilitate energy system decarbonization by incentivizing investments in clean energy technologies that meet evolving system needs. We explore market structure impacts on generator operations and deployment by risk-averse, heterogeneous investor firms using the Electricity Markets and Investment Suite - Agent-based Simulation (EMIS-AS) model. Here we apply clean energy targets of 45%-100% by 2035 considering energy, ancillary services, capacity, and clean energy credit products and pricing and eligibility rules. Results highlight a complexity conundrum, whereby finding the "right" market design to achieve decarbonization goals and avoid unintended consequences can be a highly-nuanced, non-incremental challenge. Carefully designed energy-only markets can achieve the same clean energy targets as capacity market structures but with different revenue and profitability outcomes. Operating reserve demand curve-based scarcity pricing can substitute capacity markets for similar deployment outcomes. Carbon pricing alone is most effective at achieving decarbonization levels at low clean energy targets, and clean energy credit markets and carbon pricing are substitutionary at high clean energy targets. Restricting technology participation in capacity and operating reserve markets can impact deployment and operations, even for nonrestricted technologies. Adding an inertia product with fast frequency response yields insufficient provision at high clean energy targets, but work is needed to understand frequency requirements and capabilities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Robust bidding strategy for aggregation of distributed prosumers in flexiramp market

Distributed prosumers (DPs) are the grid customers that own energy production/storage assets. Due to the flexibility and fast response of their assets, they can procure ancillary service products (ASP) in the wholesale market. An appealing ASP offered by California ISO in the real-time market (RTM) is flexiramp for which market participants do not submit direct offers, and the compensation is based on their energy opportunity costs. Here in this report, we propose a bidding strategy model for DP aggregator participation in the RTM considering energy and flexiramp. First, we develop a risk-averse optimization to determine the optimal energy and reserve product to trade in day-ahead market while considering proper amounts of flexiramp to trade in the RTM. In the RTM, to obtain optimal amounts of energy and flexiramp, the aggregator must submit hourly multi-level price-quantity energy bids for multiple RTM intervals with 15 min time-steps. On this basis, we propose a robust hourly economic bidding strategy model that determines the optimal energy bids in the RTM. We develop an adjustable robust counterpart of the model to address the RTM energy and flexiramp price uncertainties. The simulation results justify the efficacy of our proposed framework in gaining profits from the wholesale market.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Resilient NdFeB magnet recycling under the impacts of COVID-19 pandemic: Stochastic programming and Benders decomposition

Neodymium-iron-boron (NdFeB) magnets are the most powerful magnets per unit volume sold in the commercial market. Despite the increasing demand for clean energy applications such as electric vehicles and wind turbines, disruptive events including the COVID-19 pandemic have caused significant uncertainties in the supply and demand for NdFeB magnets. Therefore, this study aims to alleviate the risk of supply shortage for NdFeB magnets and the containing critical materials, rare-earth elements (REEs), through the development of a resilient reverse supply chain and logistics network design. We develop scenarios to model the unique impact of the COVID-19 pandemic on the proposed business, incorporating both disruption intensity and recovery rate. We formulate a chance-constrained two-stage stochastic programming model to maximize the profit while guaranteeing the network resiliency against disruption risks. To solve the problem in large-scale instances, we develop an efficient Benders decomposition algorithm that reduces the computational time by 98.5% on average compared to the default CPLEX algorithm. When applied to the United States, the model suggests the optimal facility locations, processing capacities, inventory levels, and material flows for NdFeB magnet recyclers that could meet 99.7% of the demand. To the best of our knowledge, this study is the first to incorporate the impacts of the COVID-19 pandemic to design a resilient NdFeB magnet recycling supply chain and logistics network, leveraging risk-averse stochastic programming.

42 ENGINEERING↗

A High-End Estimate of Sea Level Rise for Practitioners

Sea level rise (SLR) is a long-lasting consequence of climate change because global anthropogenic warming takes centuries to millennia to equilibrate for the deep ocean and ice sheets. SLR projections based on climate models support policy analysis, risk assessment and adaptation planning today, despite their large uncertainties. The central range of the SLR distribution is estimated by process-based models. However, risk-averse practitioners often require information about plausible future conditions that lie in the tails of the SLR distribution, which are poorly defined by existing models. Here, a community effort combining scientists and practitioners builds on a framework of discussing physical evidence to quantify high-end global SLR for practitioners. The approach is complementary to the IPCC AR6 report and provides further physically plausible high-end scenarios. High-end estimates for the different SLR components are developed for two climate scenarios at two timescales. For global warming of +2°C in 2100 (RCP2.6/SSP1-2.6) relative to pre-industrial values our high-end global SLR estimates are up to 0.9 m in 2100 and 2.5 m in 2300. Similarly, for a (RCP8.5/SSP5-8.5), we estimate up to 1.6 m in 2100 and up to 10.4 m in 2300. The large and growing differences between the scenarios beyond 2100 emphasize the long-term benefits of mitigation. However, even a modest 2°C warming may cause multi-meter SLR on centennial time scales with profound consequences for coastal areas. Earlier high-end assessments focused on instability mechanisms in Antarctica, while here we emphasize the importance of the timing of ice shelf collapse around Antarctica. This is highly uncertain due to low understanding of the driving processes. Hence both process understanding and emission scenario control high-end SLR.

54 ENVIRONMENTAL SCIENCES↗

A Distributionally Robust Resilience Enhancement Strategy for Distribution Networks Considering Decision-Dependent Contingencies

When performing the resilience enhancement for distribution networks, there are two obstacles to reliably model the uncertain contingencies: 1) decision-dependent uncertainty (DDU) due to various line hardening decisions, and 2) distributional ambiguity due to limited outage information during extreme weather events (EWEs). Here, to address these two challenges, this paper develops scenario-wise decision-dependent ambiguity sets (SWDD-ASs), where the DDU and distributional ambiguity inherent in EWE-induced contingencies are simultaneously captured for each possible EWE scenario. Then, a two-stage tri-level decision-dependent distributionally robust resilient enhancement (DD-DRRE) model is formulated, whose outputs include the optimal line hardening, distributed generation (DG) allocation, and proactive network reconfiguration strategy under the worst-case distributions in SWDD-ASs. Subsequently, the DD-DRRE model is equivalently recast to a mixed-integer linear programming (MILP)-based master problem and multiple scenario-wise subproblems, facilitating the adoption of a customized column-and-constraint generation (C&CG) algorithm. Finally, case studies demonstrate a remarkable improvement in the out-of-sample performance of our model, compared to its prevailing stochastic and robust counterparts. Moreover, the potential values of incorporating the ambiguity and distributional information are quantitatively estimated, providing a useful reference for planners with different budgets and risk-aversion levels.

decision-dependent uncertainty↗

A Model for Lean Corporate/ Startup Interfaces: Unlocking Resources of Midcap Corporations Providing a Pathway to Advanced Energy Technologies

Commercializing energy technologies through traditional market pathways is challenging for early-stage energy innovators. Development cycles in energy are long and expensive, and adoption is difficult, making energy technologies of limited interest to venture capital relative to industries with faster growth and shorter product life cycles such as life sciences and software. As such, partnerships with established corporations are one of the most promising, and in some cases only, go-to-market pathways for energy technologies. Startups often seek to work with, large well-known Fortune 500 (and similar) companies. However, the size and risk aversion of those firms often makes partnering challenging. It can take well over 12 months for a large corporation to agree to commercial terms and get internal board / management approval to move forward with a binding agreement with a startup for even a simple starting partnership. This timeline is prohibitive for most early-stage companies who are both time and money constrained, and often working in highly competitive commodity sectors. Mid-cap corporations ($\$ $100M to $\$ $10B) are a promising but untapped resource for partnering with technology developers because they are often nimbler, tend to be fiercely competitive, and are looking for new revenue or cost-saving opportunities. These factors make them both more receptive to disruptive technologies, and more capable of integrating them. However, while Fortune 500 companies often have venturing groups that facilitate the initial connection process, most midcap incumbents do not have the resources to create standalone corporate venture groups. As a result, although they could help each other significantly (startup technologies make midcaps more competitive; midcaps offer a faster commercialization pathway to startups), midcap companies and startups rarely work together. In 2017, ADL Ventures (ADL) received Award #DE-EE0008111 from DOE EERE’s Innovative Pathways program to unlock the domain expertise and material resources of midcap companies. The goal of the award was to support energy technology commercialization via an innovation platform for startups to interface with midcap corporations. During the grant period, we have developed a novel open innovation platform that allows financially conservative incumbents to efficiently engage with energy innovators and startups, thereby unlocking the incumbents’ domain expertise, strategic capital, R&D facilities, supply chain, and pathways to market. We have executed full-scale open innovation challenges for three clients, exceeding the initial proposed goal of two. We also built a diversified opportunity pipeline which resulted in four projects contracted for 2020, meeting the goals of the proposal, with others pending.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Early detection and uncertainty quantification of rapid sea-level rise from Antarctica

Focal Areas: (i) classification and/or anomaly detection methods applied towards identifying critical climate system thresholds; improved emulator design for (ii) reducing computational costs relative to full-physics models and (iii) improved uncertainty quantification workflows. Rationale: The evolution of the Antarctic ice sheet in response to climate change remains the single largest uncertainty in projecting future sea-level rise (SLR), with risk-averse projections for 2100 spanning between zero and a half meter. During the past decade, DOE has made substantial investments in new ice sheet and Earth system models needed to improve both understanding and predictive capability in this area. Yet major challenges remain, including better understanding when and under what circumstances significant increases in SLR from Antarctica may be initiated and better quantifying uncertainties in model-based SLR projections. Here, we discuss the potential for transformative advances in these areas through the application of machine learning and artificial intelligence (ML and AI, respectively).

54 ENVIRONMENTAL SCIENCES↗

Evaluation of In-Situ AM Process Monitoring Techniques and Potential for Detecting Process Anomalies and Undesirable Microstructures

The US Department of Energy’s Advanced Materials and Manufacturing Technologies (AMMT) program is pursuing rapid qualification of new materials for fabrication of nuclear relevant components using advanced manufacturing techniques. Particular interest is placed on code-qualifying stainless steel (SS) 316H processed by laser powder bed fusion (LPBF) additive manufacturing. A paradigm that incorporates data from in-situ sensing during the printing, ex-situ characterization, and advanced artificial intelligence–based models was established under the Transformation Challenge Reactor (TCR) program to develop a pedigree for each fabricated component that could be tracked from the feedstock to the component’s release for application. Under the TCR program, the Peregrine software was developed as a tool for incorporating the vast amounts of in-situ and ex-situ characterization data collected; all data stored on a rapidly growing digital platform. The digital platform allows for users to link site-specific process anomalies to the macro- and microstructure. The platform will eventually be able to predict component performance, which will be crucial to qualifying materials and components in risk-averse industries such as those supporting and building nuclear reactors. Current in-situ process monitoring techniques that are already integrated with software like Peregrine are advantageous for identifying process anomalies including powder spatter, component edge swelling, recoating-build interactions, and so on. However, additional data are required to fully predict the resulting microstructures needed for identifying relationships to component performance. The rapid cooling rates observed in LPBF are some of the highest of any bulk manufacturing process, resulting in heterogenous microstructures and typically causing anisotropy in mechanical properties. Moreover, evolved residual thermal stresses are high, which can cause severe defects such as delamination or cracking. Therefore, other in-situ monitoring methods are warranted for exploration to measure and map the thermal history, and potentially the stress state, of each build. This report summarizes different in-situ monitoring strategies proposed for LPBF with a focus on the more developed sensor systems. Novel capabilities for measuring melt pool temperatures are also addressed to better inform modeling efforts.

36 MATERIALS SCIENCE↗

Anticipating the reaction: public concern about sample return missions

Shifts in public attitude that may affect extraterrestrial sample return include increased public participation in the legal and regulatory environment, institutionalized public vigilance, politicization of technological debates and shifts in the nature of public decision-making, and a risk-averse public accustomed to mass media coverage that focuses on hazards and disasters. The ice-minus recombinant DNA experiment is used as an example of the effects of public opinion on scientific experimentation.

NASA Center ARC↗

Applying Formal Methods to NASA Projects: Transition from Research to Practice

NASA project managers attempt to manage risk by relying on mature, well-understood process and technology when designing spacecraft. In the case of crewed systems, the margin for error is even tighter and leads to risk aversion. But as we look to future missions to the Moon and Mars, the complexity of the systems will increase as the spacecraft and crew work together with less reliance on Earth-based support. NASA will be forced to look for new ways to do business. Formal methods technologies can help NASA develop complex but cost effective spacecraft in many domains, including requirements and design, software development and inspection, and verification and validation of vehicle subsystems. To realize these gains, the technologies must be matured and field-tested so that they are proven when needed. During this discussion, current activities used to evaluate FM technologies for Orion spacecraft design will be reviewed. Also, suggestions will be made to demonstrate value to current designers, and mature the technology for eventual use in safety-critical NASA missions.

Othon, Bill↗