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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 91 records · Page 5

Coordinating Multi-Rover Systems: Evaluation Functions for Dynamic and Noisy Environments

This paper addresses the evolution of control strategies for a collective: a set of entities that collectively strives to maximize a global evaluation function that rates the performance of the full system. Directly addressing such problems by having a population of collectives and applying the evolutionary algorithm to that population is appealing, but the search space is prohibitively large in most cases. Instead, we focus on evolving control policies for each member of the collective. The fundamental issue in this approach is how to create an evaluation function for each member of the collective that is both aligned with the global evaluation function and is sensitive to the fitness changes of the member, while relatively insensitive to the fitness changes of other members. We show how to construct evaluation functions in dynamic, noisy and communication-limited collective environments. On a rover coordination problem, a control policy evolved using aligned and member-sensitive evaluations outperfoms global evaluation methods by up to 400%. More notably, in the presence of a larger number of rovers or rovers with noisy and communication limited sensors, the proposed method outperforms global evaluation by a higher percentage than in noise-free conditions with a small number of rovers.

Turner, Kagan↗

An exploration of machine learning models for the determination of reaction coordinates associated with conformational transitions

Determining collective variables (CVs) for conformational transitions is crucial to understanding their dynamics and targeting them in enhanced sampling simulations. Often, CVs are proposed based on intuition or prior knowledge of a system. However, the problem of systematically determining a proper reaction coordinate (RC) for a specific process in terms of a set of putative CVs can be achieved using committor analysis (CA). Identifying essential degrees of freedom that govern such transitions using CA remains elusive because of the high dimensionality of the conformational space. Various schemes exist to leverage the power of machine learning (ML) to extract an RC from CA. Here, we extend these studies and compare the ability of 17 different ML schemes to identify accurate RCs associated with conformational transitions. We tested these methods on an alanine dipeptide in vacuum and on a sarcosine dipeptoid in an implicit solvent. Our comparison revealed that the light gradient boosting machine method outperforms other methods. In order to extract key features from the models, we employed Shapley Additive exPlanations analysis and compared its interpretation with the “feature importance” approach. For the alanine dipeptide, our methodology identifies ϕ and θ dihedrals as essential degrees of freedom in the C7ax to C7eq transition. For the sarcosine dipeptoid system, the dihedrals ψ and ω are the most important for the cisαD to transαD transition. We further argue that analysis of the full dynamical pathway, and not just endpoint states, is essential for identifying key degrees of freedom governing transitions.

Chemistry↗

Decentralized Failure-Tolerant Optimization of Electric Vehicle Charging

We present a decentralized failure-tolerant algorithm for optimizing electric vehicle (EV) charging, using charging stations as computing agents. The algorithm is based on the alternating direction method of multipliers (ADMM) and it has the following features: (i) It handles capacity, peak demand, and ancillary services coupling constraints. (ii) It does not require a central agent collecting information and performing coordination (e.g. an aggregator), instead all agents exchange information and computations are carried out in a fully decentralized fashion. (iii) It can withstand the failure of any number of computing agents, as long as the remaining computing agents are in a connected communications network. We construct this algorithm by reformulating the optimal EV charging problem in a decomposable form, amenable to ADMM, and then developing efficient decentralized solution methods for the subproblems dealing with coupling constraints. We conduct numerical experiments on industry-scale synthetic EV charging datasets, with up to 1,152 charging stations, using a high performance computing cluster. The experiments demonstrate that the proposed algorithm can solve the optimal EV charging problem fast enough to permit the integration of EV charging with real-time electricity markets, even in the presence of failures.

42 ENGINEERING↗

Data Quality: 1979 Southeastern Virginia Urban Plume Study (SEV-UPS): Surface and Airborne studies

The SEV-UPS field study conducted during August 1979 involved the coordinated air quality data collection efforts of three different organizations operating a total of four aircraft and 12 ground stations. Incorporated into plans for that program were numerous quality assurance activities designed to identify potential hazards for data quality in time for their correction and to take data to allow assessment of the consistency of the data from different stations. The purpose of this study was to document QA procedures that were performed by participating agencies and revise data from all platforms for mutual compatibility. For the latter effort, cases were identified on 21 occasions on seven different days where two or more monitoring systems were operating in the same location at nearly the same time. Data from the systems involved were tabulated in 200 m altitude segments, averaged and compared to detect any bias between measurements made from different systems. The results of these comparisons along with the results of independent performance audits are presented.

White, J. H.↗

Efficient Evaluation Functions for Multi-Rover Systems

Evolutionary computation can be a powerful tool in cresting a control policy for a single agent receiving local continuous input. This paper extends single-agent evolutionary computation to multi-agent systems, where a collection of agents strives to maximize a global fitness evaluation function that rates the performance of the entire system. This problem is solved in a distributed manner, where each agent evolves its own population of neural networks that are used as the control policies for the agent. Each agent evolves its population using its own agent-specific fitness evaluation function. We propose to create these agent-specific evaluation functions using the theory of collectives to avoid the coordination problem where each agent evolves a population that maximizes its own fitness function, yet the system has a whole achieves low values of the global fitness function. Instead we will ensure that each fitness evaluation function is both "aligned" with the global evaluation function and is "learnable," i.e., the agents can readily see how their behavior affects their evaluation function. We then show how these agent-specific evaluation functions outperform global evaluation methods by up to 600% in a domain where a set of rovers attempt to maximize the amount of information observed while navigating through a simulated environment.

Agogino, Adrian↗

Overview of NASA’s Science Mission Directorate Small Satellites Programs and Advances in Transformative Science Measurements with Small Satellites

Small satellites have become an accepted platform for enabling high-quality science measurements and observations. NASA missions have leveraged advances in sensor miniaturization, technology innovations, and new small satellite mission architectures to support high spatial and temporal measurements, continuity measurements, and constellations in response to science objectives described in NASA’s Decadal Surveys. Across six divisions of the Science Mission Directorate (SMD), over 12 years, SMD has funded 88 CubeSat/ SmallSat Missions and 59 Studies to date. Currently, SMD has 53 small spacecraft science missions (87spacecraft) in implementation or formulation. This paper provides the background of efforts to promote the implementation of small satellites within NASA as a balanced portfolio for the agency’s science, technology, and exploration goals. We include analysis of SmallSat awards and trends funded by SMD through Research Opportunities in Space and Earth Sciences (ROSES), Small Innovative Missions for Planetary Exploration (SIMPLEx), and Small Explorer (SMEX) and Medium Explorer (MIDEX) calls over the last 12years. The data source of this assessment is a subset of the NASA SmallSat Coordination Group Database, a collection of all known funded NASA SmallSat and CubeSat missions and studies. This paper also provides an overview of small satellite programs and selected missions from SMD’s divisions: Astrophysics, Heliophysics, Earth Science, and Planetary Science, and describes SMD’s efforts in fostering an incremental and continuous path to achieve high-priority science through transformative science measurements. This paper recognizes the latest observations and trends of the NASA CubeSat / SmallSat Science missions with masses ranging between 1kg to 500kg.

Small Satellites, SMD SmallSat, CubeSat,↗

Advances in Transformative Science Measurements with Small Satellites

Small satellites have become an accepted platform for enabling high-quality science measurements and observations. NASA missions have leveraged advances in sensor miniaturization, technology innovations, and new small satellite mission architectures to support high spatial and temporal measurements, continuity measurements, and constellations in response to science objectives described in NASA’s Decadal Surveys. Across six divisions of the Science Mission Directorate (SMD), over 12 years, SMD has funded 88 CubeSat/ SmallSat Missions and 59 Studies to date. Currently, SMD has 53 small spacecraft science missions (87spacecraft) in implementation or formulation. This paper provides the background of efforts to promote the implementation of small satellites within NASA as a balanced portfolio for the agency’s science, technology, and exploration goals. We include analysis of SmallSat awards and trends funded by SMD through Research Opportunities in Space and Earth Sciences (ROSES), Small Innovative Missions for Planetary Exploration (SIMPLEx), and Small Explorer (SMEX) and Medium Explorer (MIDEX) calls over the last 12years. The data source of this assessment is a subset of the NASA SmallSat Coordination Group Database, a collection of all known funded NASA SmallSat and CubeSat missions and studies. This paper also provides an overview of small satellite programs and selected missions from SMD’s divisions: Astrophysics, Heliophysics, Earth Science, and Planetary Science, and describes SMD’s efforts in fostering an incremental and continuous path to achieve high-priority science through transformative science measurements. This presentation recognizes the latest observations and trends of the NASA CubeSat / SmallSat Science missions with masses ranging between 1kg to 500kg.

Small Satellites, SMD SmallSat, CubeSat↗

Mineralogy of Interplanetary Dust Particles from the Comet Giacobini-Zinner Dust Stream Collections

The Draconoid meteor shower, originating from comet 21P/Giacobini-Zinner, is a low-velocity Earth-crossing dust stream that had a peak anticipated flux on Oct. 8, 2012. In response to this prediction, NASA performed dedicated stratospheric dust collections to target interplanetary dust particles (IDPs) from this comet stream on Oct 15-17, 2012 [3]. Twelve dust particles from this targeted collection were allocated to our coordinated analysis team for studies of noble gas (Univ. Minnesota, Minnesota State Univ.), SXRF and Fe-XANES (SSL Berkeley) and mineralogy/isotopes (JSC). Here we report a mineralogical study of 3 IDPs from the Draconoid collection..

Nakamura-Messenger, K.↗

Assessing the Uncertainty of Land Surface Fluxes Derived from Operational Analyses

Operational numerical weather prediction systems assimilate tremendous amounts of observations to produce global analyses of the atmospheric states. Since the systems include significant contributions from the model components, physical fields, such as the turbulent heat fluxes, can also be derived. However, the physical fields are indirectly constrained by the data assimilation, and so subject to uncertainty in the model parameterizations. Recently, 10 international operational analyses have been collected and reprocessed through the Coordinated Enhanced. Observing Period (CEOP). Comparisons against independent observations (global precipitation and outgoing longwave radiation) show that while there is significant range of the individual analyses, the ensemble of analyses provide data closest the observations. Here, we evaluate the collection of land surface turbulent heat fluxes. The data are available for Oct 2002 - Dec 2004, at 6 hourly, daily and monthly intervals. An ensemble mean and its variance have been computed. we will analyze the range of analysis results at daily and seasonal time scales, and where possible compare with existing observations.

Bosilovich, Michael G.↗

Custom-trained Machine-learning Interatomic Potentials: ZnCl2 Aqueous Solution

This dataset was generated using an iterative active-learning strategy implemented in the ArcaNN software package (https://github.com/arcann-chem/arcann_training) to train machine-learning interatomic potentials for aqueous ZnCl2 solutions. Each active-learning cycle consisted of three stages: training, exploration, and labeling. The initial training set combined configurations generated in this work from enhanced-sampling ab initio molecular dynamics simulations with configurations from a previously reported neural-network-potential study of aqueous ZnCl2. The enhanced-sampling ab initio molecular dynamics simulations involved Zn–Cl separation and the chloride coordination number around Zn²? as collective variables. These configurations served as the seed dataset. Subsequent active-learning cycles expanded the training set by identifying and labeling configurations that were poorly represented by the current models, thereby improving coverage of ion-association states and changes in local coordination and charge-state environments relevant to the solution free-energy landscape. For all selected configurations, single-point calculations of the total energies and atomic forces were performed within density functional theory using the CP2K Quickstep module. Reference calculations employed the revPBE-D3 and r2SCAN exchange-correlation functionals. Motivated by recent work on aqueous Zn²?, the main revPBE calculations omitted D3 dispersion contributions involving Zn²?, while retaining the D3 correction for water and chloride. For comparison, fully dispersion-corrected revPBE-D3 reference calculations were also performed, with D3 applied to all species, including Zn²?. Valence electrons were treated explicitly, while core electrons were represented using norm-conserving Goedecker–Teter–Hutter pseudopotentials. The wave functions were expanded using the mixed Gaussian-and-plane-wave scheme with TZV2P-MOLOPT basis sets for all elements and a 600 Ry auxiliary plane-wave cutoff for the electron density. Self-consistent-field convergence was accelerated using the orbital-transformation and Direct Inversion in the Iterative Subspace algorithms, with a convergence threshold of 10?6. All single-point calculations were performed in periodic orthorhombic cells. The CELL_REF keyword in CP2K was used to define a fixed reference cell with a box length of 25 Å. This treatment ensured a consistent reference for configurations extracted from NpT trajectories with fluctuating cell dimensions. The resulting DFT energies and atomic forces constitute the ground-truth labels used to train the MLIPs. The resulting MLIP was trained for aqueous ZnCl2 solutions spanning concentrations from 0 to 30 molal and a broad pH range, from strongly acidic to strongly basic conditions. Representative examples of configurations included in the MLIP training dataset are provided below. These include 1) Representative configurations from the dataset labeled at the revPBE-D3 level, with D3 dispersion interactions involving Zn2+ excluded (revPBE-wo-D3). 2) Representative configurations from the dataset labeled at the fully dispersion-corrected revPBE-D3 level, with D3 interactions applied to all species, including Zn2+ (revPBE-D3). 3) Representative configurations from the dataset labeled at the r2SCAN level of theory (r2SCAN).

Dinpajooh, Mohammadhasan [Pacific Northwest Nation↗

Coordinated Field Campaigns in Chesapeake Bay and Gulf of Mexico

NASA's GEOstationary Coastal and Air Pollution Events (GEO-CAPE) mission concept recommended by the U.S. National Research Council (2007) focuses on measurements of atmospheric trace gases and aerosols and aquatic coastal ecology and biogeochemistry from geostationary orbit (35,786 km altitude). Two GEO-CAPE-sponsored multi-investigator ship-based field campaigns were conducted to coincide with the NASA Earth Venture Suborbital project DISCOVER-AQ (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality) field campaigns: (1) Chesapeake Bay in July 2011 and (2) northwestern Gulf of Mexico in September 2013. Goal: to evaluate whether GEO-CAPE coastal mission measurement and instrument requirements are optimized to address science objectives while minimizing ocean color satellite sensor complexity, size and cost - critical mission risk reduction activities. NASA continues to support science studies related to the analysis of data collected as part of these coordinated field campaigns and smaller efforts.

GoMex↗

Using Coordinated, Multi-Agent Platforms for Dynamic Ocean Worlds Science

Planetary science missions have the opportunity to enhance science return through deployment of autonomous capabilities designed to dynamically respond to new information. Future outer solar system missions to ocean worlds in particular would benefit from this technology - intelligent science payloads (ISP) - because it would allow for a coordinated, near real-time response to ephemeral ‘events’ such as plumes, tectonism, surface implantation, volatile releases, thermal and magnetic anomalies, or radiation, as well as increasing the cadence and coverage of data collection. Prioritization and decision-making frameworks from ISP could be deployed at various scales - from analysis onboard a spacecraft with multiple instruments – to coordinated analyses among separate spacecraft in an e.g., distributed systems mission (DSM) composed of multiple SmallSats. Goddard’s Intelligent Science Payload team is developing an agile autonomous architecture for an icy ocean worlds DSM concept. Our goals are to coordinate data collection and onboard data analysis, and to make autonomous decisions for new data collection and analysis based on science priorities between multiple spacecraft with variable instrumentation and orbits. We use a range of data analysis tools to coordinate the DSM response, spanning from observations of data over a specified threshold to more computationally intensive machine learning algorithms (ML). ML algorithms here currently focus on determining the composition of an ocean world using mass spectrometry, and specifically methods for understanding ‘novelties’ and potential biosignatures. These algorithms could be used to quickly process and analyze onboard data that would be significantly delayed in downlink due to long communication delays for outer solar system missions in order to make dynamic science observations. Our ocean worlds case study ISP architecture is intended as an ‘agile’ and modular framework that could be used as a whole or as particular modules based on mission needs.

Distributed Systems↗

The Regolith Biters: A Divide-And-Conquer Architecture for Sample-Return Missions

The collective interaction of simple systems can be leveraged to attain complex goals. Based on this principle, we envision space system architectures where the core functional components are decoupled, autonomous, and cooperative. We aim to pursue this vision in the context of small-body sample-return missions. After all, no experimental study sheds more light into our understanding of the origin and evolution of the Solar System than the analysis of samples from asteroids and comets. We also believe that their study is important from a strategic perspective: meteorite impacts pose a direct and credible threat to life on Earth, and the development of contingency small-body deflection missions presupposes some knowledge of the target body. The current architectural paradigm for sample-return missions is centered around a design where spacecraft and sampling device are merged into a single, complex system. We argue that this monolithic approach couples the navigation and sample-collection problems, making both more difficult. In contrast, we propose a decoupled system based on the coordinated interaction between a spacecraft and a collective of small, simple devices - the Regolith Biters (RBs). A spacecraft carrying a number of RBs would travel to the vicinity of a small body. From a favorable vantage point, and while remaining within a safe distance in a non-colliding trajectory, it would release the RBs towards the target body. Upon encountering the body, they would bite the regolith (thus retaining a sample), and eject back to orbit. The spacecraft, being endowed with appropriate navigation and tracking capabilities, would rendezvous with and collect those RBs within its reach, and bring them back to Earth. Separating the navigation and sampling concerns removes the need for proximity operations with the small body-the stage in current architectures that carries the most challenges and risks. Eliminating the need for proximity operations brings back to the discussion the exploration of exciting prospects, like highly active comets, fast-rotating bodies, and binary systems. Distributing the sampling problem among a collective of agents provides the opportunity to sample multiple regions in a single mission. It also provides robustness to various environmental conditions, and may enable the distributed, in situ characterization of the body. In the search for reliability, current architectures rely on complexity: an elaborate system should succeed at once. We rely on numbers: a given agent may fail at any stage, but success is attained by the collective.

Asteroids↗

Engineering microbial consortia with rationally designed cellular interactions

Synthetic microbial consortia represent a frontier of synthetic biology that promises versatile engineering of cellular functions. They are primarily developed through the design and construction of cellular interactions that coordinate individual dynamics and generate collective behaviors. Here we review recent advances in the engineering of synthetic communities through cellular-interaction programming. We first examine fundamental building blocks for intercellular communication and unidirectional positive and negative interactions. Here, we then recap the assembly of the building blocks for creating bidirectional interactions in two-species ecosystems, which is followed by the discussion of engineering toward complex communities with increasing species numbers, under spatial contexts, and via model-guided design. We conclude by summarizing major challenges and future opportunities of engineered microbial ecosystems.

42 ENGINEERING↗

Molecular model of TFIIH recruitment to the transcription-coupled repair machinery

Transcription-coupled repair (TCR) is a vital nucleotide excision repair sub-pathway that removes DNA lesions from actively transcribed DNA strands. Binding of CSB to lesion-stalled RNA Polymerase II (Pol II) initiates TCR by triggering the recruitment of downstream repair factors. Yet it remains unknown how transcription factor IIH (TFIIH) is recruited to the intact TCR complex. Combining existing structural data with AlphaFold predictions, we build an integrative model of the initial TFIIH-bound TCR complex. We show how TFIIH can be first recruited in an open repair-inhibited conformation, which requires subsequent CAK module removal and conformational closure to process damaged DNA. In our model, CSB, CSA, UVSSA, elongation factor 1 (ELOF1), and specific Pol II and UVSSA-bound ubiquitin moieties come together to provide interaction interfaces needed for TFIIH recruitment. STK19 acts as a linchpin of the assembly, orienting the incoming TFIIH and bridging Pol II to core TCR factors and DNA. Molecular simulations of the TCR-associated CRL4CSA ubiquitin ligase complex unveil the interplay of segmental DDB1 flexibility, continuous Cullin4A flexibility, and the key role of ELOF1 for Pol II ubiquitination that enables TCR. Collectively, these findings elucidate the coordinated assembly of repair proteins in early TCR.

Paul, Tanmoy↗

Long-term multi-wavelength study of 1ES 0647+250

The BL Lac object 1ES 0647+250 is one of the few distant γ-ray emitting blazars detected at very high energies (VHEs; &100 GeV) during a non-flaring state. It was detected with the MAGIC telescopes during a period of low activity in the years 2009-2011 as well as during three flaring activities in the years 2014, 2019, and 2020, with the highest VHE flux in the last epoch. An extensive multi-instrument data set was collected as part of several coordinated observing campaigns over these years. We aim to characterise the long-term multi-band flux variability of 1ES 0647+250, as well as its broadband spectral energy distribution (SED) during four distinct activity states selected in four different epochs, in order to constrain the physical parameters of the blazar emission region under certain assumptions. We evaluated the variability and correlation of the emission in the different energy bands with the fractional variability and the Z transformed discrete correlation function, as well as its spectral evolution in X-rays and γ rays. Owing to the controversy in the redshift measurements of 1ES 0647+250 reported in the literature, we also estimated its distance in an indirect manner through a comparison of the GeV and TeV spectra from simultaneous observations with Fermi-LAT and MAGIC during the strongest flaring activity detected to date. Moreover, we interpret the SEDs from the four distinct activity states within the framework of one-component and two-component leptonic models, proposing specific scenarios that are able to reproduce the available multi-instrument data. We find significant long-term variability, especially in X-rays and VHE γ rays. Furthermore, significant (3-4σ) correlations were found between the radio, optical, and high-energy (HE) γ-ray fluxes, with the radio emission delayed by about ~400 days with respect to the optical and γ-ray bands. The spectral analysis reveals a harder-when-brighter trend during the non-flaring state in the X-ray domain. However, no clear patterns were observed for either the enhanced states or the HE (30 MeV < E < 100 GeV) and VHE γ-ray emission of the source. The indirect estimation of the redshift yielded a value of z = 0.45 ± 0.05, which is compatible with some of the values reported in the literature. The SEDs related to the low-activity state and the three flaring states of 1ES 0647+250 can be described reasonably well with the both one-component and two-component leptonic scenarios. However, the long-term correlations indicate the need for an additional radio-producing region located about 3.6 pc downstream from the gamma-ray producing region.

79 ASTRONOMY AND ASTROPHYSICS↗