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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Autonomous continuous flow reactor synthesis for scalable atom-precision

With new instrumentation design, robotics, and in-operando hyphenated analytical tool automation, the intelligent discovery of synthesis pathways is becoming feasible. It can potentially bridge the gap for the scale-up of new materials. In this article, we review current progress and describe a new system that uses an autonomous continuous flow chemistry framework to translate high-quality lead molecules and materials to quantities that can meet scalability demands. At the core is a continuous flow synthesis platform that can design its viable synthesis pathway to a particular molecule or material and then autonomously carry it out. This is realized by integrating: (1) A workflow/architecture for multimode chemical/materials characterization in-line. The in-line characterization modes are NMR, ESR, IR, Raman, UV-Vis, GC-MS, and HPLC, along with ex-situ modes for X-Ray and neutron scattering; (2) Integration for feedback/analysis/data storage of the control variables; (3) A core software stack that includes deep learning and reinforcement learning alongside quantum chemistry and molecular dynamics; (4) On-demand compute architectures that parse calculations to compute resources needed which include light-weight edge, mid-level edge (NVIDA DGX-2), and high-performance computing. We demonstrate preliminary results on how this autonomous reactor system can enhance our ability to deliver deuterated materials, copolymers, and site-substituted molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2011

Mars as a Destination in a Capability-Driven Framework

This paper describes NASA s current plans for the exploration of Mars by human crews within NASA s Capability-Driven Framework (CDF). The CDF describes an approach for progressively extending human explorers farther into the Solar System for longer periods of time as allowed by developments in technology and spacecraft systems. Within this framework, Mars defines the most challenging objective currently envisioned for human spaceflight. The paper first describes the CDF and potential destinations being considered within this framework. For destinations relevant to the exploration of Mars, this includes both the Martian surface and the two moons of Mars. This is followed by a brief review of our evolving understanding of Mars to provide the context for the specific objectives set for human exploration crews. This includes results from robotic missions and goals set for future Martian exploration by NASA's community-based forum, the Mars Exploration Program Analysis Group (MEPAG) and the MEPAG-sponsored Human Exploration of Mars - Science Analysis Group (HEM-SAG). The paper then reviews options available for human crews to reach Mars and return to Earth. This includes a discussion of the rationale used to select from among these options for envisioned Mars exploration missions. The paper then concludes with a description of technological and operational challenges that still face NASA in order to be able to achieve the exploration goals for Mars within the CDF.

Hoffman, S. J.↗
DOE OSTI2019

Big Data Framework with Machine Learning for D and D Applications - 19108

The nuclear industry is experiencing a steady increase in maintenance costs even though plants are maintained under high levels of safety, capability and reliability. Nuclear power plants are expected to run every unit at maximum capacity at all times, efficiently utilizing assets with minimal downtime. Surveillance and maintenance of nuclear decommissioning infrastructure provides lot challenges with respect to maintenance or decommissioning of the buildings. There is a need for a framework to analyze the huge amount of data generated by the sensors on the nuclear reactor components as well as structures, to monitor the conditions of these building over a period of time. Emerging technologies such as big data analytics have become a requirement in the nuclear industry to improve structural health monitoring and diagnostics. FIU will make use of existing mature technologies in the areas of imaging, robotics, big data, and machine learning/deep learning to assess the structural integrity of aging facilities at DOE sites. As these facilities await decommissioning, there is a need to understand the structural health of these structures. Many of these facilities were built over 50 years ago and in some cases these facilities have gone beyond the operational life expectancy. In other cases, the facilities have been placed in a state of 'cold and dark' and they are sitting unused, awaiting decommissioning. Finally, some older facilities are one-of-a-kind operational/production facilities supporting critical DOE missions and cannot be shut down. In any of these scenarios, the structural integrity of these facilities may be compromised, so it is imperative that adequate inspections and data collection/analysis be performed on a continuous and ongoing basis. The primary goals of the research include collecting various formats of data such as structured, unstructured and streaming data from the various sensors deployed in buildings, collect videos/pictures from various imaging sources, ingest them using a Hadoop distributed file system and process the data using Spark to perform batch processing and real time analytics. Research and development on various machine learning/deep learning algorithms will also be performed to analyze the heterogeneous data collected from nuclear decommission infrastructure. FIU will design the big data framework to ingest, store and process huge amounts of heterogeneous data collected from many sources and optimize the algorithms to provide insights into the data and predict anomalies observed when compared against baseline conditions. Various modules of this framework will include heterogeneous data sources, message broker, Hadoop distributed file system, Spark for stream and batch processing, machine learning/ deep learning, Cassandra - persistent data store and visualization. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1988

Stability analysis of multiple rigid robot manipulators holding a common rigid object

The authors consider several possible control structures for multiple-arm systems by regarding either joint torques, tip force, or a generalized acceleration of the control input. They emphasize the first case, since a class of relatively model-independent control laws can be generated for both motion and internal force control. The recently developed move/squeeze orthogonal subspace decomposition coupled with the energy Lyapunov function formulation provides a basic analytical framework within which motion and force control are considered as independent problems. Simulation results of two three-link planar arms are included to demonstrate good transient performance for both motion and force that can be attained with the full dynamics control paradigm.

Wen, John T.↗
NASA NTRS1989

On-line frequency domain information for control of a flexible-link robot with varying payload

Experimental results are given for the endpoint position control of a single-link, very flexible robot arm carrying an unknown, varying payload. The control objective is to maintain endpoint position accuracy in the presence of flexure effects after rapid movement due to a rigid body slew-angle commanded position. Fast, simple, and efficient frequency-domain schemes are used for online controller gain adjustment within an effective scheduling framework. Only endpoint acceleration and motor shaft angle measurements are utilized in relatively simple control laws where the appropriate gains have been scheduled as correlated to modal frequency information corresponding to a varying, unknown payload.

Yurkovich, Stephen↗
NASA NTRS1992

Nonlinear functional approximation with networks using adaptive neurons

A novel mathematical framework for the rapid learning of nonlinear mappings and topological transformations is presented. It is based on allowing the neuron's parameters to adapt as a function of learning. This fully recurrent adaptive neuron model (ANM) has been successfully applied to complex nonlinear function approximation problems such as the highly degenerate inverse kinematics problem in robotics.

Tawel, Raoul↗
NASA NTRS1987

Concept of adaptive structures

The concept of adaptive structures is brought up in connection with the need in ultra lightweight structural systems to maintain desired properties and configurations without human intervention when subjected to dynamic, thermal, and other environmental forces. Examples are large antenna structures and flexible robotic structures. In the both cases such adaptivity would allow less massive structural members to be employed under normal loading conditions. During special circumstances when unusually large loads are encountered, temporary stiffening would allow the use of less sturdy structures, resulting in large savings in their cost, and in increasing their mobility and efficiency. Within the framework of a finite-dimensional representation of structural dynamics, the adaptivity can be implemented by the dependence of the stiffness matrix (k) upon the expected load (Q), or expected (programmed) changes in configurations, i.e., (k) = (k(t)) where the dependence upon time is programmed in advance. In order to sustain unexpected loads the adaptive structure can be provided by feedback force control, or by a parametrical stiffness control.

Zak, Michail↗
NASA NTRS1989

How do robots take two parts apart

This research is a natural progression of efforts which begun with the introduction of a new research paradigm in machine perception, called Active Perception. There it was stated that Active Perception is a problem of intelligent control strategies applied to data acquisition processes which will depend on the current state of the data interpretation, including recognition. The disassembly/assembly problem is treated as an Active Perception problem, and a method for autonomous disassembly based on this framework is presented.

Bajcsy, Ruzena K.↗
NASA NTRS2020

Building a standardized Observing System Simulation Experiment (OSSE) framework for Mars

We advocate that the Decadal Survey recommends the NASA Science Mission Directorate to develop a rigorous Observing System Simulation Experiment (OSSE) framework for Mars, to optimize future atmospheric observations. Atmospheric conditions on Mars are a potential hazard source for landing missions. Errors in the estimates of atmospheric density profiles, inadequate knowledge of wind vertical structure and dust concentration as a function of height are likely causes of uncertainty at the landing site on the order of kilometers. An operational real-time weather forecasting capability for Mars would reduce such uncertainties, carrying enormous benefits to future robotic missions, and would be an invaluable prerequisite for human missions.A real-time forecasting capability relies upon three fundamental components: a critical mass of observing systems, a data assimilation system (DAS), and a global forecast model. The DAS allows the model to ingest the data effectively, optimizing the observational information content,and transforming them into a gridded representation of the atmosphere at a given time, called an ‘analysis’. The analysis is the best estimate of the atmospheric state for that time, and also represents a set of ‘initial conditions’ from which a global model can be initialized, to predict a future state of the atmosphere. The connection between analysis and forecast represents the foundation of modern weather forecasting. However, from the point of view of a forecast system,not all observations are equally impactful, partially because of the problem of “observational error correlation”, one important research topic in data assimilation development. For the Earth, partly due to the spontaneous and deregulated development of observations and forecast capabilities worldwide for more than half a century,the use of observations in contemporary operational forecast systems is suboptimal, with many potentially useful data being underutilized. On the contrary, Mars atmospheric scientists are in the unique situation of designing the next-generation observing systems by learning from the experience gathered on the Earth, so as to assure that the future instruments are specifically optimized to give the maximum benefit to a future weather forecast capability.An immensely powerful tool that has been firmly established by atmospheric scientists on the Earth is represented by a properly designed OSSE framework. A realistic OSSE framework cannot only quantify the benefit of future data types, be them surface based or space borne, but can also help design and optimize an entire observational network. Furthermore, OSSEs can provide deep insights into an atmosphere’s behavior, by addressing conceptual problems of its intrinsic predictability and delineating the regions or features of the atmosphere which are more sensitive to additional data and would benefit from a denser sampling. The difficulties posed by OSSEs are fundamentally different for Earth and Mars. For Earth, the enormous data volume imposes a tremendous constraint on any innovation in the observing systems: it is very hard for a single sensor to impact the skill. For Mars, the problem is the opposite: almost any additional instrument will exert some impact. However, OSSEs can help to evaluate the cost/benefit for every sensor and suggest optimal data configuration and density.The purpose of this white paper is to provide an introduction to a rigorously designed OSSE framework, explain the underlying problems and challenges, and engage the Mars community to collaborate with Earth Atmospheric scientists in order to develop a joint-OSSE framework for Mars with the largest consensual basis possible. An OSSE infrastructure would increase the understanding of the Martian atmosphere, would help NASA to optimize instrument specifications and orbit choice, providing the maximium benefit for a given expenditure of resources, and could even help establishing a roadmap for a future real-time weather forecasting capability.

Oreste Reale↗
DOE OSTI2021

A study of mechanoelectrical transduction behavior in polyvinyl chloride (PVC) gel as smart sensors

Abstract Polyvinyl chloride (PVC) gels are soft electroactive polymers (EAPs) being researched for soft robotic applications. Sensing properties of these EAPs have not been investigated in detail in regard to fundamental mechanoelectrical transduction behavior, but this smart material has been shown to exhibit a detectable response to external stimuli. This study shows PVC gels to be an extremely sensitive material when undergoing mechanoelectrical transduction and explores some response dependencies and proposes a theoretical framework for mechanoelectrical transduction within the gel. The work presented here also uncovers a very interesting phenomena under extremely low compressive loads during the initial contact with the gel. This phenomenon is attributed to a surface tension creeping motion onto the loading surface with an accompanying polarity inversion in the sensing signal relative to fully loaded gels in compression. Experimental work on hysteresis was also completed showing very little memory in steady state mechanoelectrical response to repeated stepped loading cycles. This study demonstrates the mechanoelectric ability of PVC gels to perform in sensing experiments and acts as a fundamental framework to further broaden the applications of PVC gel sensors.

Instruments & Instrumentation↗
DOE OSTI2024

Improving Self-Driving Labs: Quantifying System-Level Experiment Repeatability and Broadening Instrument-Level Compatibility

Modular Autonomous Research System (MARS) is a self-driving laboratory (SDL) which performs wet-lab science with peptide-lanthanide combinations in an automated and, ultimately, an autonomous manner to aid in soil analysis for domestic lithium mining. Autonomous experimentation involves automated experimentation, experiment planning, and active learning. MARS consists of a 6-axis robotic arm (UR5e) on a linear rail, pipette robots (Opentrons 2), and microplate readers. These components transport, operate on, and collect data with chemical solutions in standard labware. For effective autonomy, MARS must perform system-level labware operations repeatably, plan experiments autonomously, and be portable between research-domains. Repeatability is evaluated by labware placement precision, such that future operations can properly locate labware, as well as the elapsed time, so that low variance mean estimates of experiment duration can inform high-level researcher decision making. Autonomous experiment planning is the next step to decouple experimentation from human management; however, there is a conflict between the ideal system-level experiment goals and the constraints imposed by instruments’ limitations. Sub-domain portability is a long-term goal to extend MARS’ research beyond the chemistry of peptide-lanthanide binding to other sub-domains without having to invest significant overhead to system retrofitting. To address these goals, we manually trained the robotic arm labware placement and modelled statistical failurerate and uncertainty Additionally, we benchmarked the duration and variance of each experiment sub-operation as a heuristic for research decision making. Next, we use a parameterized geometric program (PGP) approach to design experiments that optimize system-level objectives and satisfy instrument-level constraints. Lastly, we proposed a Python framework to maximize MARS’ extensibility to other scientific sub-domains through a JSON-based experiment specification.

36 MATERIALS SCIENCE↗
NASA NTRS2021

System Analysis and Generative Design for Icenode, a Buoyant Vehicle for Measuring Melt Rate Under Ice Shelves

Antarctic ice shelves buttress the Antarctic Ice Sheet from sliding into the ocean, and their collapse could trigger a meter or more of global sea level rise by the end of the century. Current state-of-the-art predictions for ice shelf behavior in a warming climate have large uncertainty, significantly hindered by a lack of in situ melt rate observations under ice shelves, especially near grounding zones. IceNode is a novel robotic vehicle under development at the NASA Jet Propulsion Laboratory to acquire such measurements, but presents a complex design problem owing to the large design space and conflicting performance requirements. Evaluating a preliminary design requires several types of tedious analysis which prevents rapid iteration and exploration of the design space. We present the implementation of a custom system analysis framework which was used to automate analysis such as resource budgeting, mission simulation, mass and buoyancy balancing, and static landing stability analysis of a given design configuration. Using this framework, we selected parameters which had the largest effects on design success and conducted a generative design study in which we programmatically varied a handful of parameters to generate 1540 different design candidates and test them across 160 different environmental scenarios. The custom built system analysis tool enabled rapid development of critical analysis and automated exploration of a large design space to guide preliminary design of the IceNode vehicle.

Gebara, Christine↗
DOE OSTI2022

Using genetic algorithms to systematically improve the synthesis conditions of Al-PMOF

The synthesis of metal-organic frameworks (MOFs) is often complex and the desired structure is not always obtained. In this work, we report a methodology that uses a joint machine learning and experimental approach to optimize the synthesis conditions of Al-PMOF (Al 2 (OH) 2 TCPP) [H 2 TCPP = meso-tetra(4-carboxyphenyl)porphine], a promising material for carbon capture applications. Al-PMOF was previously synthesized using a hydrothermal reaction, which gave a low throughput yield due to its relatively long reaction time (16 hours). Here, we use a genetic algorithm to carry out a systematic search for the optimal synthesis conditions and a microwave-based high-throughput robotic platform for the syntheses. We show that, in just two generations, we could obtain excellent crystallinity and yield close to 80% in a much shorter reaction time (50 minutes). Moreover, by analyzing the failed and partially successful experiments, we could identify the most important experimental variables that determine the crystallinity and yield.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1991

Systems engineering studies of lunar base construction

Many ingenious concepts have been proposed for lunar base construction, but few systematic studies exist which relate time-consistent lunar base construction technologies and the choice of lunar base approach with the long-term SEI objectives - i.e., lunar indigenous base construction and Mars Exploration equipment development. To fill this gap, CSC has taken a two-pronged approach. First, the Center undertook basic geotechnical investigations of lunar soil, fabrication of a scale prototype of a lunar construction crane, a multi-robot construction team laboratory experiment, and a preliminary design of lunar base structures. Second, during Jun. and Jul. 1991 two lunar base construction systems engineering studies were accomplished - a 'near term lunar base' study, and a 'far-term lunar base' study. The goals of these studies were to define the major lunar base construction research problems in consistent technology/construction frameworks, and to define design requirements for construction equipment such as a lunar crane and a regolith mover. The 'near-term lunar base' study examined three different construction concepts for a lunar base comprised of pre-fabricated, pre-tested, Space Station Freedom-type modules, which would be covered with regolith shielding. Concept A used a lunar crane for unloading and transportation; concept B, a winch and cart; and concept C, a walker to move the modules from the landing site to the base site and assemble them. To evaluate the merits of each approach, calculations were made of mass efficiency measure, source mass, reliability, far-term base mass, Mars base mass, and base assembly time. The model thus established was also used to define the requirements for crane speed and regolith mover m(sup 3)/sec rates. A major problem addressed is how to 'mine' the regolith and stack it over the habitats as shielding. To identify when the cost of using indigenous lunar materials to construct the base exceeds the cost of development and delivery of the equipment for processing lunar materials, a study of construction of a candidate sintered regolith 'far term lunar base' was undertaken. A technique was devised for casting slabs of sintered (basaltic) regolith and assembling these into a hemispherical (or geodesic) dome. The major problem occurs with the inner liner. At 14.7 psi and 20 percent oxygen internal atmosphere, the entire structure is in tension, even with the regolith load. Also, another study has indicated that at 14.7 psi major resupply of air will be needed because of leakage, and astronauts may have to engage in extensive pre-breathing and post-breathing for extravehicular activity (EVA) tasks, thus detracting from useful mission work time. An alternative is to operate part of the base at, say, 5 psi and 70 percent oxygen, or to equip the astronauts with hard suits at 8.3 psi or greater. All of these choices directly influence base design and construction techniques.

Morgenthaler, George W.↗
NASA NTRS2006

The State of Space Propulsion Research

The current state of space propulsion research is assessed from both a historical perspective, spanning the decades since Apollo, and a forward-looking perspective, as defined by the enabling technologies required for a meaningful and sustainable human and robotic exploration program over the forthcoming decades. Previous research and technology investment approaches are examined and a course of action suggested for obtaining a more balanced portfolio of basic and applied research. The central recommendation is the establishment of a robust national Space Propulsion Research Initiative that would run parallel with systems development and include basic research activities. The basic framework and technical approach for this proposed initiative are defined and a potential implementation approach is recommended.

Sackheim, R. L.↗
NASA NTRS2008

Targeting and Localization for Mars Rover Operations

A design and a partially developed application framework were presented for improving localization and targeting for surface spacecraft. The program has value for the Mars Science Laboratory mission, and has been delivered to support the Mars Exploration Rovers as part of the latest version of the Maestro science planning tool. It also has applications for future missions involving either surface-based or low-altitude atmospheric robotic vehicles. The targeting and localization solutions solve the problem of how to integrate localization estimate updates into operational planning tools, operational data product generalizations, and flight software by adding expanded flexibility to flight software, the operations data product pipeline, and operations planning tools based on coordinate frame updates during a planning cycle.

Powell, Mark W.↗
NASA NTRS2004

The Robotic Lunar Exploration Program (RLEP): An Introduction to the Goals, Approach, and Architecture

The Vision for Space Exploration calls for undertaking lunar exploration activities to enable sustained human and robotic exploration of Mars and beyond, including more distant destinations in the solar system. In support of this vision, the Robotic Lunar Exploration Program (RLEP) is expected to execute a series of robotic missions to the Moon, starting in 2008, in order to pave the way for further human space exploration. This paper will give an introduction to the RLEP program office, its role and its goals, and the approach it is taking to executing the charter of the program. The paper will also discuss candidate architectures that are being studied as a framework for defining the RLEP missions and the context in which they will evolve.

Watzin, James G.↗
DOE OSTI2024

A multiscale anisotropic polymer network model coupled with phase field fracture

The study of polymers has continued to gain substantial attention due to their expanding range of applications, spanning essential engineering fields to emerging domains like stretchable electronics, soft robotics, and implantable sensors. These materials exhibit remarkable properties, primarily stemming from their intricate polymer chain network, which, in turn, increases the complexity of precisely modeling their behavior. Especially for modeling elastomers and their fracture behavior, accurately accounting for the deformations of the polymer chains is vital for predicting the rupture in highly stretched chains. Despite the importance, many robust multiscale continuum frameworks for modeling elastomer fracture tend to simplify network deformations by assuming uniform behavior among chains in all directions. Recognizing this limitation, our study proposes a multiscale fracture model that accounts for the anisotropic nature of elastomer network responses. At the microscale, damage in the chains is assumed to be driven by both the chain's entropy and the internal energy due to molecular bond distortions. In order to bridge the stretching in the chains to the macroscale deformation, we employ the maximal advance path constraint network model, inherently accommodating anisotropic network responses. As a result, chains oriented differently can be predicted to exhibit varying stretch and, consequently, different damage levels. To drive macroscale fracture based on damages in these chains, we utilize the micromorphic regularization theory, which involves the introduction of dual local-global damage variables at the macroscale. The macroscale local damage variable is obtained through the homogenization of the chain damage values, resulting in the prediction of an isotropic material response. The macroscale global damage variable is subjected to nonlocal effects and boundary conditions in a thermodynamically consistent phase field continuum formulation. Moreover, the total dissipation in the system is considered to be mainly due to the breaking of the molecular bonds at the microscale. To validate our model, we employ the double-edge notched tensile test as a benchmark, comparing simulation predictions with existing experimental data. Additionally, to enhance our understanding of the fracturing process, we conduct uniaxial tensile experiments on a square film made up of polydimethylsiloxane (PDMS) rubber embedded with a hole and notches and then compare our simulation predictions with the experimental observations. Furthermore, we visualize the evolution of stretch and damage values in chains oriented along different directions to assess the predictive capacity of the model. In conclusion, the results are also compared with another existing model to evaluate the utility of our model in accurately simulating the fracture behavior of rubber-like materials.

42 ENGINEERING↗