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At least 307 records · Page 17

Exploration Medical Capability - Advancing Medical System Design and Risk-Informed Decision Making for Deep Space Exploration

BACKGROUND: Within NASA’s Human Research Program, the Exploration Medical Capability (ExMC) Element has three primary focus areas: clinical and scientific research, systems engineering and trade space analysis, and technology development and demonstrations. These focus areas feed into the overarching goal of enabling progressively Earth-Independent Medical Operations (EIMO), a new paradigm that will be necessary for future Artemis and Mars medical and vehicle systems. This EIMO end state aligns with NASA’s Moon to Mars Objectives, which clearly outline the need for NASA deep space exploration missions to reduce their reliance upon Earth and become increasingly autonomous, in preparation for the first human Mars mission. OVERVIEW: To advance exploration medical systems and ultimately, integrated crew health and performance systems, ExMC’s portfolio includes: funding ground development & testing of novel medical capabilities; creation of new approaches for the development of medical protocols and procedures; deployment of innovative technologies into analog environments; technology demonstrations in spaceflight; and eventual transition to operations of new capabilities for deep space exploration missions. The portfolio also includes: pharmaceutical research targeting stability, pharmacokinetics, and pharmacodynamics; integrated data architectures and clinical decision support tools; and systems engineering and trade space analysis tools to assist NASA in the development of future medical system models as well as the medical system requirements that can serve as a foundation for deep space exploration missions. All of these investments are done in a collaborative and coordinated fashion with other NASA stakeholders, such as the Environmental Control and Life Support Systems – Crew Health and Performance System Capability Leadership Team and the Health and Medical Technical Authority. DISCUSSION: In this presentation, ExMC will provide an overview of our work from across our portfolio, all of which will inform future EIMO efforts at NASA. ExMC’s research and development investments are targeted to reduce the human system risks associated with deep space exploration to the Moon and Mars.

Kris Lehnhardt↗

Space Station Freedom accommodation of the Human Exploration Initiative

The design requirements of the Space Station Freedom (SSF) are proposed based on the requirements and assumptions of the Human Exploration Initiative. In this summary of a NASA study consideration is given to the mission-supporting capabilities needed to sustain support of a continuous human presence in earth orbit for scientific activities. The initial SSF configuration (called Assembly Complete) is found to be insufficient in terms of the optimal provisions for crew size, power, pressurized volume, and truss structure. Specific design requirements are also given for the Lunar Transfer Vehicle, and the checkout of this vehicle creates additional demands on the SSF facilities. General specifications are given for the SSF modules, vehicle processing, remote manipulator, and mobile transporter within the context of a continuous human presence in orbit.

Meredith, Barry D.↗

Using Space Weather Variability in Evaluation the Radiation Environment Specifications for NASA's Constellation Program

Hardware design environments for NASA's Constellation Program-the Vision for Space Exploration program to design and build new vehicles for servicing low Earth orbit and the Moon and beyond-have been developed that are necessarily conservative in nature to assure robust hardware design and development required to build space systems which will meet operational goals in a wide range of space environments, This presentation will describe the rationale used to establish the space radiation and plasma design environments specified for a variety of applications including total ionizing radiation dose, dose rate effects, and spacecraft charging and will compare the design environments with "space weather" variability to evaluate the applicability of the design environments and potential vulnerabilities of the system to extreme space weather events.

Coffey, Victoria N.↗

Moving the needle: Employing deep reinforcement learning to push the boundaries of coarse-grained vaccine models

Highly mutable infectious disease pathogens (hm-IDPs) such as HIV and influenza evolve faster than the human immune system can contain them, allowing them to circumvent traditional vaccination approaches and causing over one million deaths annually. Agent-based models can be used to simulate the complex interactions that occur between immune cells and hm-IDP-like proteins (antigens) during affinity maturation—the process by which antibodies evolve. Compared to existing experimental approaches, agent-based models offer a safe, low-cost, and rapid route to study the immune response to vaccines spanning a wide range of design variables. However, the highly stochastic nature of affinity maturation and vast sequence space of hm-IDPs render brute force searches intractable for exploring all pertinent vaccine design variables and the subset of immunization protocols encompassed therein. To address this challenge, we employed deep reinforcement learning to drive a recently developed agent-based model of affinity maturation to focus sampling on immunization protocols with greater potential to improve the chosen metrics of protection, namely the broadly neutralizing antibody (bnAb) titers or fraction of bnAbs produced. Using this approach, we were able to coarse-grain a wide range of vaccine design variables and explore the relevant design space. Our work offers new testable insights into how vaccines should be formulated to maximize protective immune responses to hm-IDPs and how they can be minimally tailored to account for major sources of heterogeneity in human immune responses and various socioeconomic factors. Our results indicate that the first 3 to 5 immunizations, depending on the metric of protection, should be specially tailored to achieve a robust protective immune response, but that beyond this point further immunizations require only subtle changes in formulation to sustain a durable bnAb response.

60 APPLIED LIFE SCIENCES↗

Power Converter Circuit Design Automation using Parallel Monte Carlo Tree Search

The tidal waves of modern electronic/electrical devices have led to increasing demands for ubiquitous application-specific power converters. A conventional manual design procedure of such power converters is computation- and labor-intensive, which involves selecting and connecting component devices, tuning component-wise parameters and control schemes, and iteratively evaluating and optimizing the design. To automate and speed up this design process, we propose an automatic framework that designs custom power converters from design specifications using Monte Carlo Tree Search. Specifically, the framework embraces the upper-confidence-bound-tree (UCT), a variant of Monte Carlo Tree Search, to automate topology space exploration with circuit design specification-encoded reward signals. Moreover, our UCT-based approach can exploit small offline data via the specially designed default policy and can run in parallel to accelerate topology space exploration. Further, it utilizes a hybrid circuit evaluation strategy to substantially reduce design evaluation costs. Empirically, we demonstrated that our framework could generate energy-efficient circuit topologies for various target voltage conversion ratios. Compared to existing automatic topology optimization strategies, the proposed method is much more computationally efficient --- the sequential version can generate topologies with the same quality while being up to 67% faster. Here, the parallelization schemes can further achieve high speedups compared to the sequential version.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Conceptual Design Aspects of Three General Sub-Classes of Multi-Rotor Configurations: Distributed, Modular, and Heterogeneous

Quadcopters and other multi-rotor configurations are poised to make a substantial contribution to commercial and public service aviation. Small multi-rotor configurations already see almost ubiquitous use as radio-controlled toys and hobbyist platforms. In particular, their use as flying cameras has seen rapid adoption by the public. But their greatest contribution to our society may likely be seen in public service missionsapplications. Their potential utility for supporting emergency response missions is discussed in some detail. The multi-rotor design space is then explored from high-level perspective with the emphasis on distributed, modular, and heterogeneous multi-rotor systems. Following this design space examination, a number of specific, detailed technical issues related multi-rotor conceptual design and sizing is also considered.

Configurations↗

An Altair Overview: Designing a Lunar Lander for 21st Century Human Space Exploration

Altair, the lunar lander element of NASA's Constellation program, was conducted in a different design environment than many other NASA projects of similar scope. Because of this relatively unique approach, there are a number of significant success stories that should be considered during the development of any future lunar landers or human spacecraft. This paper is divided into two separate themes; the first is the approach used during the conceptual design studies, including the systematic analysis cycles and the decision making process associated with each: and the second is a summary of the resulting lessons learned that were compiled after looking back at the lifetime of the Project. Altair was terminated before entering Phase B of its design, and was often criticized for being a very heavy and very large vehicle. While there was specific rationale for all of the decisions that led up to that configuration, future design cycles were specifically planned to re-address the mass challenge. Had the project continued, the deliberate, stepwise design process would have converged on an optimized lander design that balanced mass, risk, cost and capabilities. Some of the specific items that will be addressed in this paper include project development strategy, organizational approach and team dynamics, risk-informed design process, mission architecture constraints, mission key driving requirements, model-based systems engineering process, configuration studies, contingency considerations, subsystem overviews and key trade studies. The paper will conclude with a summary of the lessons identified during the Altair project and make suggestions for application to future studies.

Brown, Kendall K.↗

NASA Docking System Block 1: NASA's New Direct Electric Docking System Supporting ISS and Future Human Space Exploration

The NASA Docking System (NDS) Block 1 is a key component of NASA's vision for space exploration. It is designed to provide capability for visiting vehicles to dock to the International Space Station's recently-installed International Docking Adapter ports. It is the first docking system to be developed by NASA since the Apollo-Soyuz Test Project of the 1970's. The NDS Block 1 includes provisions for capture, structural attachment, power/data transfer, and undocking. It uses a direct-drive electromechanical Stewart Platform capture system architecture, along with an innovative automated control scheme, to achieve an unprecedented level of performance and simplicity. Its design implements the new International Docking System Standard, which will be a key enabler of diverse and flexible exploration missions in future iterations. NDS qualification was completed in 2017 to support a planned first flight in 2018 on the Boeing CST-100 Starliner.

NASA Docking System↗

Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design

Conspectus The variability of chemical bonding in open-shell transition-metal complexes not only motivates their study as functional materials and catalysts but also challenges conventional computational modeling tools. Here, tailoring ligand chemistry can alter preferred spin or oxidation states as well as electronic structure properties and reactivity, creating vast regions of chemical space to explore when designing new materials atom by atom. Although first-principles density functional theory (DFT) remains the workhorse of computational chemistry in mechanism deduction and property prediction, it is of limited use here. DFT is both far too computationally costly for widespread exploration of transition-metal chemical space and also prone to inaccuracies that limit its predictive performance for localized d electrons in transition-metal complexes. These challenges starkly contrast with the well-trodden regions of small-organic-molecule chemical space, where the analytical forms of molecular mechanics force fields and semiempirical theories have for decades accelerated the discovery of new molecules, accurate DFT functional performance has been demonstrated, and gold-standard methods from correlated wavefunction theory can predict experimental results to chemical accuracy. The combined promise of transition-metal chemical space exploration and lack of established tools has mandated a distinct approach. In this Account, we outline the path we charted in exploration of transition-metal chemical space starting from the first machine learning (ML) models (i.e., artificial neural network and kernel ridge regression) and representations for the prediction of open-shell transition-metal complex properties. The distinct importance of the immediate coordination environment of the metal center as well as the lack of low-level methods to accurately predict structural properties in this coordination environment first motivated and then benefited from these ML models and representations. Once developed, the recipe for prediction of geometric, spin state, and redox potential properties was straightforwardly extended to a diverse range of other properties, including in catalysis, computational “feasibility”, and the gas separation properties of periodic metal–organic frameworks. Interpretation of selected features most important for model prediction revealed new ways to encapsulate design rules and confirmed that models were robustly mapping essential structure–property relationships. Encountering the special challenge of ensuring that good model performance could generalize to new discovery targets motivated investigation of how to best carry out model uncertainty quantification. Distance-based approaches, whether in model latent space or in carefully engineered feature space, provided intuitive measures of the domain of applicability. With all of these pieces together, ML can be harnessed as an engine to tackle the large-scale exploration of transition-metal chemical space needed to satisfy multiple objectives using efficient global optimization methods. In practical terms, bringing these artificial intelligence tools to bear on the problems of transition-metal chemical space exploration has resulted in ML-model assessments of large, multimillion compound spaces in minutes and validated new design leads in weeks instead of decades.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multidisciplinary Systems Analysis of a Six Passenger Quadrotor Urban Air Mobility Vehicle Powertrain

There is a high degree of research interest in the design space for electric vertical takeoff and landing (eVTOL) vehicles, because these vehicles are seen as key enablers for urban air mobility (UAM). This work further explores the eVTOL design space, by presenting analysis of a six-passenger eVTOL quadrotor powertrain, with integrated power, propulsion, and thermal management systems modeled using the Numerical Propulsion System Simulation (NPSS) and the NPSS Power System Library. Four architectures are modeled at the same design point and compared over a design mission. Results from an architecture comparison study show that a hybrid architecture performs best in terms of cruise range, however, the hybrid needs batteries with high specific energy and specific power in order to obtain a benefit vs turboelectric architectures. Sensitivity studies are conducted to show correlations between component parameters and system metrics. This data provides useful indicators for further technological improvement. Lastly, an initial TMS model is presented, and sensitivity studies on TMS design parameters are presented as well, to show high level TMS design trends.

electrified propulsion↗

Multidisciplinary Systems Analysis of a Six Passenger Quadrotor Urban Air Mobility Vehicle Powertrain

There is a high degree of research interest in the design space for electric vertical takeoff and landing (eVTOL) vehicles, because these vehicles are seen as key enablers for urban air mobility (UAM). This work further explores the eVTOL design space, by presenting analysis of a six-passenger eVTOL quadrotor powertrain, with integrated power, propulsion, and thermal management systems modeled using the Numerical Propulsion System Simulation (NPSS) and the NPSS Power System Library. Four architectures are modeled at the same design point and compared over a design mission. Results from an architecture comparison study show that a hybrid architecture performs best in terms of cruise range, however, the hybrid needs batteries with high specific energy and specific power in order to obtain a benefit vs turboelectric architectures. Sensitivity studies are conducted to show correlations between component parameters and system metrics. This data provides useful indicators for further technological improvement. Lastly, an initial TMS model is presented, and sensitivity studies on TMS design parameters are presented as well, to show high level TMS design trends.

evtol↗

Reliability-Informed Economic and Energy Evaluation for Bi-Level Design for Remanufacturing: A Case Study of Transmission and Hydraulic Manifold

Abstract Design for remanufacturing (DfRem) is one attractive strategy that encourages the reuse of a product and extends the product's life cycle. Traditional design processes often only consider product reliability at an early design stage. However, from the perspective of environmental sustainability, it is becoming increasingly important to evaluate the long-term economic and environmental impacts of design decisions during early-stage design. We propose a bi-level DfRem framework consisting of system-level reusability allocation and component-level design tradeoff analysis, considering reliability and product warranty policy. First, a system-level reusability allocation problem aims at a theoretical exploration of the design space where all the components comprising the system are allocated certain reuse rates to achieve target energy savings with minimum cost. Following the theoretical exploration at the system level, a component-level analysis looks at practical design options for each component and trades-off between the overall cost and energy consumption for multiple remanufacturing cycles. Both levels of the framework require modeling component reuse for multiple remanufacturing cycles, which we achieve by using a branched power-law model that provides probabilistic scenarios of reusing the component or replacing it with a new part. We demonstrate the utility of this framework with the case study of an infinitely variable transmission (IVT) used by some agricultural machines manufactured by John Deere and show snapshots of a prototype software tool that we developed for easy use by designers.

Engineering↗

Creep-Fatigue Relationsihps in Electroactive Polymer Systems and Predicted Effects in an Actuator Design

The paper concerns the time-dependent behavior of electroactive polymers (EAP) and their use in advanced intelligent structures for space exploration. Innovative actuator design for low weight and low power valves required in small plants planned for use on the moon for chemical analysis is discussed. It is shown that in-depth understanding of cyclic loading effects observed through accelerated creep rates due to creep-fatigue interaction in polymers is critical in terms of proper functioning of EAP based actuator devices. In the paper, an overview of experimental results concerning the creep properties and cyclic creep response of a thin film piezoelectric polymer polyvinylidene fluoride (PVDF) is presented. The development of a constitutive creep-fatigue interaction model to predict the durability and service life of electroactive polymers is discussed. A novel method is proposed to predict damage accumulation and fatigue life of polymers under oyclic loading conditions in the presence of creep. The study provides a basis for ongoing research initiatives at the NASA Kennedy Space Center in the pursuit of new technologies using EAP as active elements for lunar exploration systems.

Vinogradov, Aleksandra M.↗

Exploration-Related Research on the International Space Station: Connecting Science Results to the Design of Future Missions

In January, 2004, the US President announced a vision for space exploration, and charged NASA with utilizing the International Space Station (ISS) for research and technology targeted at supporting the US space exploration goals. This paper describes: 1) what we have learned from the first four years of research on ISS relative to the exploration mission, 2) the on-going research being conducted in this regard, 3) our current understanding of the major exploration mission risks that the ISS can be used to address, and 4) current progress in realigning NASA s research portfolio for ISS to support exploration missions. Specifically, we discuss the focus of research on solving the perplexing problems of maintaining human health on long-duration missions, and the development of countermeasures to protect humans from the space environment, enabling long duration exploration missions. The interchange between mission design and research needs is dynamic, where design decisions influence the type of research needed, and results of research influence design decisions. The fundamental challenge to science on ISS is completing experiments that answer key questions in time to shape design decisions for future exploration. In this context, exploration-relevant research must do more than be conceptually connected to design decisions-it must become a part of the mission design process.

Rhatigan, Jennifer L.↗

Data-Driven Discovery of Linear Molecular Probes with Optimal Selective Affinity for PFAS in Water

Approaches to tackle the wide and growing variety of highly persistent per- and polyfluoroalkyl substances (PFAS) are of pressing global need because of their detrimental human health effects, such as cancer, birth defects, and hormone imbalance. Sensitive, selective, and easy-to-use real-time sensors to monitor and detect PFAS and sorbents to extract them are critical to meeting government-mandated environmental concentrations. In this work, we combine all-atom molecular dynamics simulations, enhanced sampling, deep representational learning, and Bayesian optimization to perform high-throughput virtual screening for highly sensitive and selective molecular probes. Our molecular design space consists of 3850 linear hydrocarbon chains with varying degrees of halogenation with and without amine- and phosphine-based headgroups. By employing a data-driven search process, we efficiently explore the molecular design space to optimize the sensitivity to perfluorooctanesulfonic acid (PFOS) as a prototypical PFAS analyte and selectivity relative to a sodium dodecyl sulfate (SDS) interferent. We calculate 504 Gibbs free energies of probe-analyte and probe-interferent interactions and identify probes with PFOS association free energies of up to (-ΔG PFOS ) = 9.8 ± 0.2 kJ/mol and selectivities relative to SDS of (-ΔΔG PFOS–SDS ) = 3.1 ± 1.5 kJ/mol. A C 11 Br 23 P(CH 3 ) 2 probe containing 11 backbone brominated carbons and a tertiary phosphine headgroup possesses the most sensitive binding constant to PFOS within the defined search space of K b PFOS = 177.4 ± 12.7, and a semibrominated probe C 5 H 11 C 7 Br 14 N(CH 3 ) 2 containing 12 backbone carbons and a tertiary amine headgroup possesses the highest selectivity relative to SDS of K b PFOS /K b SDS = 4.6 ± 1.7. A retrospective analysis of our data to extract interpretable design rules reveals that the sensitivity of linear hydrogenated probes increases by approximately 1 kJ/mol per C–C bond. The addition or removal of halogen atoms and amine or phosphine headgroups produces nonmonotonic changes in both sensitivity and selectivity with changes to the sensitivity of up to 2.5 kJ/mol. Finally, this work places empirical limitations on the performance of a wide range of linear probes for PFOS detection and offers a generic strategy for high-throughput computational screening to promote selective and sensitive binding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗