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1,637 records · Page 91

Evaluating Global Emission Inventories of Biogenic Bromocarbons

Emissions of halogenated very short-lived substances (VSLS) are poorly constrained. However, their inclusion in global models is required to simulate a realistic inorganic bromine (Bry) loading in both the troposphere, where bromine chemistry perturbs global oxidizing capacity, and in the stratosphere, where it is a major sink for ozone (O3). We have performed simulations using a 3-D chemical transport model (CTM) including three top-down and a single bottom-up derived emission inventory of the major brominated VSLS bromoform (CHBr3) and dibromomethane (CH2Br2). We perform the first concerted evaluation of these inventories, comparing both the magnitude and spatial distribution of emissions. For a quantitative evaluation of each inventory, model output is compared with independent long-term observations at National Oceanic and Atmospheric Administration (NOAA) ground-based stations and with aircraft observations made during the NSF (National Science Foundation) HIAPER Pole-to-Pole Observations (HIPPO) project. For CHBr3, the mean absolute deviation between model and surface observation ranges from 0.22 (38 %) to 0.78 (115 %) parts per trillion (ppt) in the tropics, depending on emission inventory. For CH2Br2, the range is 0.17 (24 %) to 1.25 (167 %) ppt. We also use aircraft observations made during the 2011 Stratospheric Ozone: Halogen Impacts in a Varying Atmosphere (SHIVA) campaign, in the tropical western Pacific. Here, the performance of the various inventories also varies significantly, but overall the CTM is able to reproduce observed CHBr3 well in the free troposphere using an inventory based on observed sea-to-air fluxes. Finally, we identify the range of uncertainty associated with these VSLS emission inventories on stratospheric bromine loading due to VSLS (Br(VSLS/y)). Our simulations show Br(VSLS/y) ranges from approximately 4.0 to 8.0 ppt depending on the inventory. We report an optimized estimate at the lower end of this range (approximately 4 ppt) based on combining the CHBr3 and CH2Br2 inventories which give best agreement with the compilation of observations in the tropics.

bromocarbons↗

A Custom Machine to Convey Radiologically Impacted Cohesive Soils to the Orion ScanSortSM System - 20382

An established method to reduce the volume of material required to be disposed of as radioactive waste is conveyor-based sorting of potentially radiologically impacted soils. With the Orion ScanSortSM system, potentially impacted soils are conveyed beneath radiation detectors and sorted into above and below criteria bins based on the detectors' response. Confident measurements can only be efficiently achieved when the soil column being conveyed has a reasonably consistent geometry. Highly cohesive soils present a very significant challenge as they tend to clump and adhere to the conveyor hopper, strike-off bar, and belt skirting. This causes voids and valleys in the soil column that affect the measurement geometry and reduce the confidence in the measurement. The reduction in confidence necessitates a longer residence time (i.e. reduction in conveyor belt speed and processing rates) or that the soils in highly unfavorable geometries be dispositioned as impacted or segregated for resurvey (should site logistics support that option). These outcomes may increase the volume of material required to be dispositioned as radiological waste and have a negative impact on project cost and schedule. To minimize impact to sorting operations, Wood designed and built a customized Extruder, to optimize the soil column prior to assay. The design was developed and refined to minimize the volume of highly cohesive soils presented in highly unfavorable geometries in the soil column in order to confidently assess and disposition such soils in a high-production environment. The Extruder is a customized 90 cm wide flat conveyor that has an oversized hopper with a pair of motor-driven rollers that force the soils in the hopper through an opening of adjustable height. The soils are extruded through the opening to produce a soil column that is ∼75 cm wide and ∼8-18 cm deep with a design rate of 225 metric tons/hr. The Extruder was recently deployed with the Orion ScanSort{sup SM} System to a site in northeast Ohio. The site has highly cohesive soils that result from the weathering of glacial sediments and consist of clay and clay loam, resulting in poor drainage and high moisture content. The project infrastructure only supported two bins of material (above and below criteria), which necessitated that soils with unfavorable geometries be discharged into the above criteria bin, along with material determined to have been contaminated. The Extruder was extremely successful in producing a stable soil column with favorable geometries for radiological assay. During production, less than 0.5% (by mass) of the soils processed were presented in unsatisfactory geometries requiring disposition as radioactive waste. The Extruder did not get clogged due to the cohesive soils (as is typical with conventional conveyors) and required very little maintenance, again minimizing impacts to sorting operations. The conveyor belt speed was operated at 14 cm/s with a typical belt loading of ∼109 kg/m resulting in a mean process rate of ∼49 metric tons/hr. The process rate was constrained by other project logistics, rather than by the capabilities of the Extruder, which was operated at less than 20% of the maximum design speed (75 cm/s). It is concluded that the Extruder is highly likely to produce a stable highly cohesive soil column suitable for efficient and confident radiological assay in production environments of 250 short tons/hr or more. The Extruder has the capability to drastically reduce the duration and costs of projects with radiologically impacted highly cohesive soils. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Investigation of aerodynamic design issues with regions of separated flow

Existing aerodynamic design methods have generally concentrated on the optimization of airfoil or wing shapes to produce a minimum drag while satisfying some basic constraints such as lift, pitching moment, or thickness. Since the minimization of drag almost always precludes the existence of separated flow, the evaluation and validation of these design methods for their robustness and accuracy when separated flow is present has not been aggressively pursued. However, two new applications for these design tools may be expected to include separated flow and the issues of aerodynamic design with this feature must be addressed. The first application of the aerodynamic design tools is the design of airfoils or wings to provide an optimal performance over a wide range of flight conditions (multipoint design). While the definition of 'optimal performance' in the multipoint setting is currently being hashed out, it is recognized that given a wide range of flight conditions, it will not be possible to ensure a minimum drag constraint at all conditions, and in fact some amount of separated flow (presumably small) may have to be allowed at the more demanding flight conditions. Thus a multipoint design method must be tolerant of the existence of separated flow and may include some controls upon its extent. The second application is in the design of wings with extended high speed buffet boundaries of their flight envelopes. Buffet occurs on a wing when regions of flow separation have grown to the extent that their time varying pressures induce possible destructive effects upon the wing structure or adversely effect either the aircraft controllability or passenger comfort. A conservative approach to the expansion of the buffet flight boundary is to simply expand the flight envelope of nonseparated flow under the assumption that buffet will also thus be alleviated. However, having the ability to design a wing with separated flow and thus to control the location, extent and severity of the separated flow regions may allow aircraft manufacturers to gain an advantage in the early design stages of an aircraft, when configuration changes are relatively inexpensive to make. The goal of the summer research at NASA Langley Research Center (LaRC) was twofold: first, to investigate a particular airfoil design problem observed under conditions of strong shock induced flow separation on the upper surface of an airfoil at transonic conditions; and second, to suggest and investigate design methodologies for the prediction (or detection) and control of flow separation. The context of both investigations was to use an existing two dimensional Navier-Stokes flow solver and the constrained direct/iterative surface curvature (CDISC) design algorithm developed at LaRC. As a lead in to the primary task, it was necessary to gain a familiarity with both the design method and the computational analysis and to perform the FORTRAN coding needed to couple them together.

Gally, Tom↗

Sparse chronology strategy for integrating seasonal energy storage in capacity expansion models

Here, this study develops the sparse chronology method to enhance the representative period framework in capacity expansion models, enabling the effective integration of long-duration energy storage modeling. Traditional representative period methods cannot capture the state of charge of seasonal energy storage systems because they do not establish effective inter-day linkages to connect the state of charge between periods. The sparse chronology approach addresses this limitation by establishing inter-day linkages that allow state of charge to shift inter-seasonally. At the same time, it groups identical representative days into partitions, applying constraints sparsely and implicitly to reduce computational load further. Validation results demonstrate that this method successfully simulates long-duration energy storage patterns, achieving close alignment with a continuous yearly benchmark model, with seasonal trends and state of charge cycles clearly represented. The computational load analysis reveals that the sparse chronology method efficiently applies constraints on maximum and minimum state of charge limits within the representative day framework, eliminating the need for detailed constraints on each individual day. By partitioning representative days and constraining only the start and end of each partition, the method significantly decreases computational requirements. Simulation results show that sparse chronology closely approximates the continuous yearly method's accuracy, even with as few as 20 representative days, achieving correlation values with the benchmark of nearly 0.9 in state of charge plots. Furthermore, it maintains computational efficiency, requiring only 4 % of the solver time compared to the continuous yearly method with 20 representative days. This approach allows capacity expansion models to incorporate long-duration energy storage with high temporal, spatial, and technological resolution, enabling more detailed modeling for large-scale power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Towards Erecting Straighter Lightweight Towers on the Moon Using Deployable Guy Wires

This paper reports our static stability test findings for a simple guy wire system to correct the natural lateral deflections of an 8.5m tall, compact deployable composite tower intended to support exploration of lunar permanently shadowed regions by nearby robotic assets. Deployable composite booms with microgravity flight heritage are currently being investigated at NASA Langley Research Center (LaRC) and Massachusetts Institute of Technology(MIT)’s Space Resources Workshop for their potential to be vertically deployed in the lunar gravity field, in support of NASA’s Artemis campaign. These applications include vertical solar arrays and the provision of elevated lines-of-sight to science or engineering payloads on landers and rovers, in support of nearby or distant crewed or robotic assets exploring scientifically interesting and hard to reach areas. Useful elevated payloads include radio repeaters, remote sensing and imaging, navigation and power beaming systems. However, while these lightweight booms have an excellent height to mass ratio, they typically exhibit slight axial curvature upon deployment resulting in appreciable lateral dead-load deflection of the tip mass relative to the tower base. This static deflection increases with tower height and tip mass, not only constraining the value delivered by the tower but also endangering its integrity. To develop a competitive, lightweight deployable composite boom tower, a capability to correct static deflections during and after deployment may be required. This paper presents a pathfinder deployable guy wire stability system for the MIT / LaRC self-erecting composite boom lunar tower that provides real time measurements, maintains tension passively, and can serve as a reconfigurable platform to test new guy wire components, configurations and control algorithms. Using a validated, calibrated photogrammetry system, the natural lateral deflection of the boom tip relative to the boom base at different deployed heights in Earth’s gravity field was recorded. With real-time tension measurements it was found that guy wires can significantly reduce the tip deflection of a deployable composite boom under dead load. Specifically, we found that (1) control capability is greatest where it is needed most, i.e. for the lever arm closest to being opposite the direction of deflection, and (2) for a tower height of at least 8.5 m and arm length of at least 60 cm, a solution of differential tension in all three arms exists and, in principle, provides sufficient control capability to correct or significantly reduce boom deflections. We also found that natural deflections occur almost entirely out-of-plane of the seams of the boom cross-section, which was expected, and that the natural boom tip lateral deflection under dead load upon deployment was ~5% of boom deployed length, unexpectedly exceeding the manufacturing acceptance specification of 1%.Ongoing and future collaborative work between LaRC and MIT includes the further investigation of the unexpected lateral deflection, testing of alternative guy wire system designs at higher tensions and higher deployed heights, as well as trade studies of costs and benefits of an optimized integrated guywire system compared to other types of static stability solutions.

lunar towers↗

A solution framework for linear PDE-constrained mixed-integer problems

Abstract We present a general numerical solution method for control problems with state variables defined by a linear PDE over a finite set of binary or continuous control variables. We show empirically that a naive approach that applies a numerical discretization scheme to the PDEs to derive constraints for a mixed-integer linear program (MILP) leads to systems that are too large to be solved with state-of-the-art solvers for MILPs, especially if we desire an accurate approximation of the state variables. Our framework comprises two techniques to mitigate the rise of computation times with increasing discretization level: First, the linear system is solved for a basis of the control space in a preprocessing step. Second, certain constraints are just imposed on demand via the IBM ILOG CPLEX feature of a lazy constraint callback. These techniques are compared with an approach where the relations obtained by the discretization of the continuous constraints are directly included in the MILP. We demonstrate our approach on two examples: modeling of the spread of wildfire and the mitigation of water contamination. In both examples the computational results demonstrate that the solution time is significantly reduced by our methods. In particular, the dependence of the computation time on the size of the spatial discretization of the PDE is significantly reduced.

97 MATHEMATICS AND COMPUTING↗

Trajectory Design Considerations for Exploration Mission 1

Exploration Mission 1 (EM-1) will be the first mission to send an uncrewed Orion Multi-Purpose Crew Vehicle (MPCV) to cislunar space in the fall of 2019. EM-1 was originally conceived as a lunar free-return mission, but was later changed to a Distant Retrograde Orbit (DRO) mission as a precursor to the Asteroid Redirect Mission. To understand the required mission performance (i.e., propellant requirement), a series of trajectory optimization runs was conducted using JSC's Copernicus spacecraft trajectory optimization tool. In order for the runs to be done in a timely manner, it was necessary to employ a parallelization approach on a computing cluster using a new trajectory scan tool written in Python. Details of the scan tool are provided and how it is used to perform the scans and post-process the results. Initially, a scan of daily due east launched EM-1 DRO missions in 2018 was made. Valid mission opportunities are ones that do not exceed the useable propellant available to perform the required burns. The initial scan data showed the propellant and delta-V performance patterns for each launch period. As questions were raised from different subsystems (e.g., power, thermal, communications, flight operations, etc.), the mission parameters or data that were of interest to them were added to the scan output data file. The additional data includes: (1) local launch and landing times in relation to sunrise and sunset, (2) length of eclipse periods during the in-space portion of the mission, (3) Earth line of sight from cislunar space, (4) Deep Space Network field of view looking towards cislunar space, and (5) variation of the downrange distance from Earth entry interface to splashdown. Mission design trades can also be performed based on the information that the additional data shows. For example, if the landing is in darkness, but the recovery operations team desires a landing in daylight, then an analysis is performed to determine how to change the mission design to meet this request. Also, subsystems request feasibility of alternate or contingency mission designs, such as adding an Orion main engine checkout burn or Orion completing all of its burns using only its auxiliary thrusters. This paper examines and presents the evolving trade studies that incorporate subsystem feedback and demonstrate the feasibility of these constrained mission trajectory designs and contingencies.

Dawn, Timothy F.↗

Clinical Decision Support Project

As NASA plans for exploration missions into deep space, significant challenges are realized due to the distance from Earth. Beside the effects of microgravity and radiation exposure, the astronauts face the additional constraints of isolation, lack of resupply, increasingly difficult evacuation, and delayed and disrupted communication with ground-based medical care providers. These constraints require a paradigm shift from current medical care where crews rely on the real-time communications with ground-based medical care providers toward Earth-independent medical operations for astronaut medical care. Medical expertise and decision-making are ground-based for current International Space Station and planned Lunar missions. However, a deep space exploration crew will need to autonomously perform the detection, diagnosis, treatment, and prevention of medical conditions. One approach to provide Earth-independent medical operations is to augment the requisite knowledge, skills, and abilities (KSAs) of a time-constrained crew—operating under stressful conditions, combatting fatigue, and facing a potential medical crisis—with a robust clinical decision support system (CDSS). The CDSS is envisioned as an integrated, software-based tool deployed on a laptop computer or handheld device. The CDSS will assist the crew and ground support when interacting with knowledge/data bases (e.g. records, pharmacy, schedule), instrumentation (e.g. imaging, physiological monitoring devices), and habitat (e.g. wellness system, task performance system) and vehicle systems (e.g. environmental system, communication system). In addition, the human interface will employ a context-based approach that accounts for the crew’s situation. Thus, extraneous and clinically/operationally non-relevant information are reduced to avoid an increase in cognitive load. The framework of an ideal spaceflight CDSS is to include core and advanced analytical features that maintain a flexible platform for integrating new technology in the future. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) is expanding the boundaries of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit by actively identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addressed ap Medical-701 within the Inflight Medical Conditions risk: “We need to increase inflight medical capabilities and identify new capabilities that (a) maximize benefit and/or (b) reduce “costs” on human system/mission/vehicle resources.” Though mass, volume, and power will face increasing constraints, the projected computational capabilities of spacecraft systems will increase exponentially as information technology advances in this decade and beyond. Hence, data, software, and computational resources will play an essential and synergistic role in maintaining crew health, wellness, and performance in deep space missions. The focus of the CDS project was to develop recommended requirements for an in-vehicle CDSS that acts as a ‘virtual assistant’ for delivering optimal health, performance, and medical care during exploration missions. In fiscal year 2022 (FY22), the CDS project was chartered to baseline and/or revise all CDS project related documentation and update the CDS project model to include the revised CDSS Concept of Operations, revised systems-based modeling language (SysML) activity diagrams, and baseline requirements. The focus of this presentation will be an overview of the CDS products and CDS model content.

Decision Support↗

Dynamic Charging Rendezvous and Motion Planning for a Multi-AGV Team Including a Mobile Charging Host

Teams of automated battery-powered electric vehicles have the potential to execute complex mission tasks in off-road environments for agriculture, military, and other applications. Limited onboard energy reserves hinder their adoption in large-scale resource-constrained environments, where recharging is a necessity. It may be infeasible to install a network of static charging stations in off-road environments. For this reason, dedicated mobile host vehicles with charging capabilities are proposed as a means to increase range and capabilities of the multivehicle team. Here, in this study, we consider an ad hoc planning framework, where results from a high-confidence trajectory planner are leveraged to plan charging rendezvous between a host and other worker vehicles in a receding horizon fashion to provide high confidence that energy reserves will not be prematurely exhausted. The core problem is posed so as to minimize the impact of recharging on the mission in terms of task delays, overall energy utilization, and costs of fast charging. Through extensive Monte Carlo simulations of an off-road mission, we show a decrease in task delays without substantial increases in energy needs by updating the charging rendezvous plan during the mission. However, if updates are made too often, model mismatch may cause unnecessary cycling and mission failure.

Energy constraints↗

Spline-Based Smoothing of Airfoil Curvatures

Constrained fitting for airfoil curvature smoothing (CFACS) is a splinebased method of interpolating airfoil surface coordinates (and, concomitantly, airfoil thicknesses) between specified discrete design points so as to obtain smoothing of surface-curvature profiles in addition to basic smoothing of surfaces. CFACS was developed in recognition of the fact that the performance of a transonic airfoil is directly related to both the curvature profile and the smoothness of the airfoil surface. Older methods of interpolation of airfoil surfaces involve various compromises between smoothing of surfaces and exact fitting of surfaces to specified discrete design points. While some of the older methods take curvature profiles into account, they nevertheless sometimes yield unfavorable results, including curvature oscillations near end points and substantial deviations from desired leading-edge shapes. In CFACS as in most of the older methods, one seeks a compromise between smoothing and exact fitting. Unlike in the older methods, the airfoil surface is modified as little as possible from its original specified form and, instead, is smoothed in such a way that the curvature profile becomes a smooth fit of the curvature profile of the original airfoil specification. CFACS involves a combination of rigorous mathematical modeling and knowledge-based heuristics. Rigorous mathematical formulation provides assurance of removal of undesirable curvature oscillations with minimum modification of the airfoil geometry. Knowledge-based heuristics bridge the gap between theory and designers best practices. In CFACS, one of the measures of the deviation of an airfoil surface from smoothness is the sum of squares of the jumps in the third derivatives of a cubicspline interpolation of the airfoil data. This measure is incorporated into a formulation for minimizing an overall deviation- from-smoothness measure of the airfoil data within a specified fitting error tolerance. CFACS has been extensively tested on a number of supercritical airfoil data sets generated by inverse design and optimization computer programs. All of the smoothing results show that CFACS is able to generate unbiased smooth fits of curvature profiles, trading small modifications of geometry for increasing curvature smoothness by eliminating curvature oscillations and bumps (see figure).

Li, W.↗

Constraining Interlayer Slipping in P2-Type Layered Oxides with Oxygen Redox by Constructing Strong Covalent Bonds

Lattice oxygen redox (LOR) in P2-type layered oxides is an effective strategy to break through the limit of energy density of conventional cathodes due to its high redox potential (>4 V vs. Na + /Na) as well as extra capacity. Nevertheless, LOR induced local structure distortion and irreversible phase transitions cause serious electrochemical performance degradation, hindering the practical applications. In this work, we propose that the generation of the OP4 phase can be replaced with the Z phase by introducing Sb element with higher ionic potential and strong covalent bonds within the TMO 6 octahedron. Z phase transition is realized by constraining interlayer slipping between adjacent TM layers compared to OP4, which reduces the strain in the layered structure, lowers the Na+ diffusion energy barrier and creates more efficient Na+ diffusion channels. Consequently, Sb-substituted oxides demonstrates excellent kinetics, rate capability (79 mAh g -1 at 1 A g -1 ) in half cell and a high energy density of 487 Wh kg -1 (on cathode) in full cell.

25 ENERGY STORAGE↗

Scalable Techniques for Stochastic Power Flow Problems (Final Report)

The proposed research focuses on developing scalable algorithms for two-stage security-constrained OPF problems with AC power flow constraints, a class of problems complicated by (i) scale arising from a scenario representation; and (ii) the presence of nonlinearity, nonconvexity, and possibly second-stage discreteness or complementarity. Unfortunately, most existing solvers cannot contend with both challenges simultaneously; accordingly, the proposed research focuses on developing solution techniques that can both scale with the number of scenarios and contend with nonconvexity and second-stage complementarity. We consider three avenues for addressing such problems: (i) Variable sample-size SQP (VS-SQP) methods that combine sparse Quasi-Newton updates with a scalable variance-reduced stochastic gradient scheme for stochastic QP subproblems, allowing for contending with second-stage complementarity via regularization; (ii) Variable sample-size stochastic Interior-point (VS-sIP) schemes that propose a sampling-based regularized (to allow for contending with complementarity) interior-point schemes in which a Schur-complement technique is employed for decomposing the Newton direction computation step; (iii) Variable sample-size tractable ADMM (VS-tADMM) schemes combine variable sample-sizes with carefully designed techniques for resolving each of the nonconvex updates (by leveraging the QCQP structures). We intend to compare the three schemes using performance profiles in terms of solution quality, scalability, etc. and then select one scheme which will then be developed and further refined in Python for purposes of the GO competition.

42 ENGINEERING↗

Least-Cost Pathways for India's Electric Power Sector

The Government of India has a target of deploying 175 GW from renewable energy by 2022 and 40% of electricity capacity from renewable energy by 2030 and has indicated that ambitions for 2030 could be higher. Rapid changes in technology costs and performance could drive further deployment of wind and solar capacity beyond these policy targets. Increased deployment of variable renewable energy (VRE) raises new questions for power system planning regarding the optimal siting of generation capacity, trade-offs between generation and transmission infrastructure, and system flexibility needs. This study aims to evaluate least-cost pathways for India's electric power system over the period 2017-2047. Uniquely, this work considers an expanded planning horizon and range of scenarios not previously analyzed in national planning studies in India. The data collection and model design processes undertaken for this study provides a framework for recurring planning studies. This study finds anticipated changes in electricity demand and component costs can drive a significant shift in India's future electricity supply and how this system will be operated. In the Base scenario, the share of generation from VRE reaches 54% by 2047. Reducing the capital cost of wind has a larger impact on VRE penetration than reducing the capital cost of solar PV or battery storage. In the lowest wind cost scenario (40% capital cost decline by 2047 relative to the Base scenario), the penetration of VRE in the generation mix reaches 722%, exceeding the penetration levels achieved when the cost of battery storage or solar PV are reduced by an even greater 50%. In a future system with high penetrations of RE, capacity additions are driven by the coincidence of demand and RE generation rather than peak demand alone. This study finds the system could have surplus capacity during the peak demand months of July–September because this period corresponds to periods with high wind speeds and more wind generation available to meet peak demand. By contrast, new capacity is needed to meet demand during moderate demand months of October–November when output from wind plants falls more than 75% nationally compared to the previous two months. Finally, the success for gas for electricity production may depend on cost competitiveness rather than fuel availability. Increasing the amount of gas available for electricity production had no significant impact on the capacity or generation mix by 2047, as determined from a scenario that significantly increases fuel availability throughout the planning horizon. In fact, over 80% of new gas fuel available for the power sector remains unused. This suggests the high cost of gas plant operations relative to other technologies may constrain the expansion of gas generation in India more than fuel availability.

14 SOLAR ENERGY↗

SWIRP (Submm-Wave and Long Wave InfraRed Polarimeter); Development and Characterization of a Sub-Mm Polarimeter for Ice Cloud Investigations

A major source of uncertainty in climate models is the presence, shape and distribution of ice particles in the uppermost layers of the clouds. The effects of this component are poorly constrained, turning ice particles into an almost-free variable in many climate models.NASA-GSFC is developing a new instrument aimed at measuring the size and shape of ice particles. The instrument consists of two sub-mm polarimeters (at 220 and 670 GHz) coupled with a long-wave infrared polarimeter at 10 micron. Each polarimeter has identical V-pol and H-pol channels; the axes of polarization are defined geometrically by the orientation of the waveguide elements, and the purity has been measured in the lab. The instrument is configured as a conical scanner, suitable for deployment as a payload on a small satellite or on a high-altitude sub-orbital platform. From a 400 km orbit, the instrument has a 3dB spatial resolution of 20 (10) km at 220 (670) GHz and a swath of 600 km over 180 degrees of view.The BAPTA (Bearing And Power Transfer Assembly) carries heritage from the SSMIS design, now in its 22nd year of on-orbit operation, but with a much reduced SWaP (Size Weight and Power) footprint, suitable for a small satellite.The main components of the instrument have been fabricated and are undergoing final testing prior to their integration as a single unit. The sub-mm channels have dedicated secondary reflectors which illuminate a shared primary reflector. The receiving units are placed behind the focal point of the optical arrangement, so that all beams equally illuminate the primary reflector and are almost co-located on the ground (within a single 220 GHz footprint). Primary and secondary beam patterns have been measured and verified to match the as-designed expectations. A Zytex (TM) window is deployed to protect the secondary reflectors and the feed horns from debris and other contaminants, and to reduce the heat load from the active (hot) IR calibration unit. The insertion loss of Zytex has been measured and is accounted in the calibration equation of the sub-mm channels.The radiometric performance of the sub-mm receivers has been characterized in the lab and under operational conditions of temperature and pressure.This paper discusses the design constraints on the sub-mm components, details of the scientific goals and their flowdown, and describes the characterization of the polarimeters. Options to optimize the layout and distribution of the masses within the assembly, with the goal of making the instrument even more compact and fully-compatible with cubesat-class satellites will be presented.

De Amici, G.↗

Convergent Manufacturing of Large-Scale Components for Nuclear Applications, via Additive Manufacturing and Powder Metallurgy Hot Isostatic Pressing

Powder metallurgy (PM)–hot isostatic pressing (PM-HIP) has long been recognized as a powerful route for producing fully dense, near net shape metallic components. By consolidating powders under high temperature and pressure, HIP provides isotropic properties, uniform microstructures, and scalability to complex geometries that are vital for sectors such as aerospace, energy, and nuclear power. Yet despite these advantages, the technology has remained constrained by costly trial and error canister fabrication, limitations of conventional forging, and incomplete knowledge about how the canister design influences final part properties. Additive manufacturing (AM), by contrast, thrives on design freedom and geometric flexibility but struggles with speed, scalability, and cost when applied to very large structures. The research presented in this report investigated how a convergent manufacturing approach, combining AM with PM-HIP, can merge the strengths of both technologies, leveraging AM’s flexibility for canister design and HIP’s consolidation capability to deliver reliable, large, and complex parts. The work progressed through three case studies that built on one another in scale and complexity. Small cylindrical canisters fabricated by conventional methods, laser powder bed fusion, and directed energy deposition were filled with stainless steel powders and subjected to HIP. The resulting parts demonstrated near-full density and mechanical properties on par with wrought stainless steel, showing for the first time that AM canisters can be a direct substitute for conventional ones without sacrificing quality. The next step involved a medium-scale, noncentrosymmetric T-valve, which is an enclosed, multibranch geometry that tested the limits of AM + PM-HIP integration. The T-valve achieved predictable shrinkage and uniform densification, confirming feasibility for enclosed designs. However, this study also revealed oxide inclusions and interfacial challenges at the AM + HIP boundary, underscoring the critical importance of controlling interface chemistry and employing robust, in situ strategies, such as melt pool monitoring and thermal monitoring, coupled with nondestructive evaluation techniques such as x-ray computed tomography. Finally, the effort culminated in fabricating a large-scale impeller weighing nearly 2000 lb and spanning 5 ft in diameter. Produced via multirobot wire arc AM and hot isostatic pressed to near-full density, the impeller validated industrial-scale feasibility. Predictive models closely matched experimental shrinkage, tensile properties were spatially uniform across the component, and the AM + PM-HIP interface proved mechanically sound despite the presence of oxide-decorated prior particle boundaries. This large-scale demonstration is a major milestone, showing that hybrid AM + PM‑HIP can reliably deliver components at reactor-relevant scales. Collectively, these studies charted a logical pathway: small-scale work built scientific confidence, medium-scale work highlighted opportunities and challenges, and large-scale work proved industrial impact. The overarching conclusion of this report is that AM + PM-HIP should not be seen as a replacement for forging but as a complementary pathway that provides the US with flexibility, resilience, and new options for manufacturing nuclear-grade components. Looking ahead, several directions emerge as critical to sustaining progress. Predictive modeling must become faster, more accessible, and more accurate, with digital twins and machine learning reducing reliance on trial and error. Powders and alloys must be optimized for HIP, with improved cleanliness, reduced oxides, and tailored chemistries that enhance creep, fatigue, and irradiation resistance. Interfaces between AM and HIP regions must be better engineered through coatings, machining strategies, and surface treatments to mitigate oxide formation and ensure reliable bonding to explore opportunities for HIP of targeted compositional parts, as well as multimaterial HIP cladding applications. Monitoring and nondestructive evaluation need to expand, incorporating multimodal sensors, x-ray computed tomography, and real-time data integration through platforms such as Pelican. At the same time, the pathway to industrial adoption requires techno-economic analysis, machinability studies, and qualification frameworks aligned with industry and regulatory standards. Finally, workforce and academic engagement must be strengthened. Programs that train technicians and engineers for US Navy and US Department of Energy manufacturing challenges should be paired with academic partnerships to support fundamental research, with open sharing of non-export-controlled data to accelerate innovation and build the next generation of experts. In conclusion, this report demonstrates that hybrid AM + PM-HIP is scientifically viable and strategically important. By combining the design agility of AM with the consolidation strength of HIP and embedding modeling, monitoring, and workforce development, this approach provided a transformative new capability for US manufacturing. The path forward is clear: hybrid AM + PM-HIP is not just a promising research direction but is also potentially an industrially relevant pathway that can reshape how nuclear-grade components are designed, qualified, and deployed.

36 MATERIALS SCIENCE↗

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

J Lemery↗

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

Medical Operations↗