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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Active workflow system for near real-time extreme-scale science. In: PPAA '14 Proceedings of the first workshop on Parallel programming for analytics applications

In recent years, streaming-based data processing has been gaining substantial traction for dealing with overwhelming data generated by real-time applications, from both enterprise sources and scientific computing. In this work, however, we look at an emerging class of scientific data with Near Real-Time (NRT) requirement, in which data is typically generated in a bursty fashion with the near real-time constraints being applied primarily between bursts, rather than within a stream. A key challenge for this types of data sources is that the processing time per data element is not uniform, and not always feasible to predict. Given the observations on the increasing unpredictability of compute load and system dynamics, this work looks to adapt streaming-based approach to the context of this new class of large experiments and simulations that have complex run-time control and analysis issues. In particular, we deploy a novel two-tier scheme for handling the increasing unpredictability of runtime behaviors: Instead of relying on determining what and where to run the scientific workflows beforehand or partial dynamically, the decision will also be adaptively enhanced online according to system runtime status. This is enabled by embedding workflow along with data streams. Specifically, we break data outputs generated from experiments or simulations into multiple self-describing "chunks", which we call active data objects. As such, if there is a transient hotspot observed, a data object with unfinished workflow pipeline can break its previous schedule and search for a least loaded location to continue the execution. Our preliminary experiment results based on synthetic workloads demonstrate the proposed active workflow system as a very promising solution by outperforming the state-of-the-art semi-dynamic workflow schedulers with an improved workflow completion time, as well as a good scalability.

Zhang, Yanwei↗
NASA NTRS1982

Galileo spacecraft power distribution and autonomous fault recovery

There is a trend in current spacecraft design to achieve greater fault tolerance through the implemenation of on-board software dedicated to detecting and isolating failures. A combination of hardware and software is utilized in the Galileo power system for autonomous fault recovery. Galileo is a dual-spun spacecraft designed to carry a number of scientific instruments into a series of orbits around the planet Jupiter. In addition to its self-contained scientific payload, it will also carry a probe system which will be separated from the spacecraft some 150 days prior to Jupiter encounter. The Galileo spacecraft is scheduled to be launched in 1985. Attention is given to the power system, the fault protection requirements, and the power fault recovery implementation.

Detwiler, R. C.↗
NASA NTRS2007

Ares Launch Vehicles Lean Practices Case Study

The Ares launch vehicles team, managed by the Ares Projects Office (APO) at NASA Marshall Space Flight Center, has completed the Ares I Crew Launch Vehicle System Requirements Review and System Definition Review and early design work for the Ares V Cargo Launch Vehicle. This paper provides examples of how Lean Manufacturing, Kaizen events, and Six Sigma practices are helping APO deliver a new space transportation capability on time and within budget, while still meeting stringent technical requirements. For example, Lean philosophies have been applied to numerous process definition efforts and existing process improvement activities, including the Ares I-X test flight Certificate of Flight Readiness (CoFR) process, risk management process, and review board organization and processes. Ares executives learned Lean practices firsthand, making the team "smart buyers" during proposal reviews and instilling the team with a sense of what is meant by "value-added" activities. Since the goal of the APO is to field launch vehicles at a reasonable cost and on an ambitious schedule, adopting Lean philosophies and practices will be crucial to the Ares Project's long-term SUCCESS.

Doreswamy, Rajiv↗
NASA NTRS2008

Estimating the Need for Medical Intervention due to Sleep Disruption on the International Space Station

During ISS and shuttle missions, difficulties with sleep affect more than half of all US crews. Mitigation strategies to help astronauts cope with the challenges of disrupted sleep patterns can negatively impact both mission planning and vehicle design. The methods for addressing known detrimental impacts for some mission scenarios may have a substantial impact on vehicle specific consumable mass or volume or on the mission timeline. As part of the Integrated Medical Model (IMM) task, NASA Glenn Research Center is leading the development of a Monte Carlo based forecasting tool designed to determine the consumables required to address risks related to sleep disruption. The model currently focuses on the International Space Station and uses an algorithm that assembles representative mission schedules and feeds this into a well validated model that predicts relative levels of performance, and need for sleep (SAFTE Model, IBR Inc). Correlation of the resulting output to self-diagnosed needs for hypnotics, stimulants, and other pharmaceutical countermeasures, allows prediction of pharmaceutical use and the uncertainty of the specified prediction. This paper outlines a conceptual model for determining a rate of pharmaceutical utilization that can be used in the IMM model for comparison and optimization of mitigation methods with respect to all other significant medical needs and interventions.

Myers, Jerry G.↗
DOE OSTI2017

Simplified Models for Accelerated Structural Prediction of Conjugated Semiconducting Polymers

We perform molecular dynamics simulations of poly(benzodithiophene-thienopyrrolodione) (BDT-TPD) oligomers in order to evaluate the accuracy with which unoptimized molecular models can predict experimentally characterized morphologies. The predicted morphologies are characterized using simulated grazing-incidence X-ray scattering (GIXS) and compared to the experimental scattering patterns. We find that approximating the aromatic rings in BDT-TPD with rigid bodies, rather than combinations of bond, angle, and dihedral constraints, results in 14% lower computational cost and provides nearly equivalent structural predictions compared to the flexible model case. The predicted glass transition temperature of BDT-TPD (410 +/- 32 K) is found to be in agreement with experiments. Predicted morphologies demonstrate short-range structural order due to stacking of the chain backbones (p-p stacking around 3.9 A), and long-range spatial correlations due to the self-organization of backbone stacks into 'ribbons' (lamellar ordering around 20.9 A), representing the best-to-date computational predictions of structure of complex conjugated oligomers. We find that expensive simulated annealing schedules are not needed to predict experimental structures here, with instantaneous quenches providing nearly equivalent predictions at a fraction of the computational cost of annealing. We therefore suggest utilizing rigid bodies and fast cooling schedules for high-throughput screening studies of semiflexible polymers and oligomers to utilize their significant computational benefits where appropriate.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1993

A neural based intelligent flight control system for the NASA F-15 flight research aircraft

A flight control concept that can identify aircraft stability properties and continually optimize the aircraft flying qualities has been developed by McDonnell Aircraft Company under a contract with the NASA-Dryden Flight Research Facility. This flight concept, termed the Intelligent Flight Control System, utilizes Neural Network technology to identify the host aircraft stability and control properties during flight, and use this information to design on-line the control system feedback gains to provide continuous optimum flight response. This self-repairing capability can provide high performance flight maneuvering response throughout large flight envelopes, such as needed for the National Aerospace Plane. Moreover, achieving this response early in the vehicle's development schedule will save cost.

Urnes, James M.↗
NASA NTRS2006

Internal Structure of Rhea

We model the interior of Rhea on the basis of observational constraints and the results from geodynamical models available in the literature. Ten main types of models are defined, depending on the presence or absence of a high-pressure ice layer (ice II), and the extent of separation of the rock component from the volatiles. The degree-two gravity coefficients are computed for each of these models in order to assess which properties of the interior are likely to be inferred from Cassini radio science measurements scheduled on 26 November 2005. C22 greater than 2.5 x 10(exp -4) indicates that the satellite is undifferentiated, except for a slight increase in density with depth resulting from material self-compression. C22 between 1.67 x 10(exp -4)(lower bound) and 1.90 x 10(exp -4) indicates the presence of a rocky core, whose radius can be determined from the satellite's mass and ices densities, for a given temperature profile. For other values, most of the ten models cannot be distinguished from each other. However, assumptions on the density of the rock phase, presence or absence of ice II, and the degree of differentiation could allow a unique model to be determined in many cases. While the calculation presented in this work assumes that Rhea is in hydrostatic equilibrium, it is likely that Rhea' gravity field is partly affected by nonhydrostatic anomalies.

gravity science↗
NASA NTRSDate not supplied

Preliminary Design of an 'Autonomous Medical Response Agent' Interface Prototype for Long Duration Spaceflight

Major challenges for astronauts in future long-duration exploration missions (LDEMs) will be that crewmembers are not expected to be medical professionals, may be under high workload and stress, are facing physiological challenges caused by spaceflight, and will have limited, delayed voice communications with medical support from Earth. An autonomous medical response agent (AMRA) is envisioned to help astronauts address medical complaints, develop a differential diagnosis, and guide self-treatment until a healthy state is restored. AMRA develops a process of personalized diagnosis and treatment through a Bayesian predictive control system that recommends therapeutic control actions including diagnostic tests and treatments to crewmembers (Menon, 2020). The Human Computer Interaction (HCI) lab from NASA Ames Research Center’s Human Systems Integration Division (Code TH) has collaborated with Nahlia Inc in human-centered design augmentation research for AMRA. The project, titled Design of ‘Autonomous Medical Response Agent Interface Prototype for Long Duration Spaceflight, has been funded by the Translational Research Institute for Space Health (TRISH) and introduces an interactive user-interface prototype that guides astronauts through self-diagnosis, treatment, and rehabilitation while communicating with remote specialists in ground support (most notably a patient’s flight surgeon). Our project develops the interaction design for the crewmember using AMRA through user research, iterative design, and usability testing to evaluate the user interface and workflow designed. The interface design deliverable for this project, titled AMRA Aggregate Information Display (AMRA AID) is an integrated information display system for comprehensive autonomous medical guidance, diagnosis, and treatment of in-flight medical conditions experienced by crewmembers. AMRA AID demonstrates how we might ensure crew autonomy, increase the crew’s medical capabilities, and decrease cognitive burden within a front-end user interface. AMRA AID refrains from relying on input from ground or mission control for self-treatment of medical issues—though ground awareness and communication with ground is maintained as a means of ensuring trust between mission control and crew. AMRA AID demonstrates how the crew’s on-board medical system might integrate with information from vehicle monitoring and crew schedule, without assuming causal relationships. AMRA AID’s comprehensive view enables efficient information access for both crew and ground support, reducing cognitive burden in the event of an unplanned or emergency medical incident and enabling informed analytical decisions to be made based on both crew and vehicle health. Human-centered design augmentation advanced within the prototype included: enhanced workflow and treatment guidance for two medical scenarios for a non-specialist user base with various levels of medical training, interaction design which considered speech (conversational user interface) elements and on-screen interactions to be developed in future iterations of the project, communication design and functional requirements relevant to self-care versus caring for another astronaut, as well as user testing of the prototype with an international space medical community. This project arrives at critical findings regarding usability needs, communication requirements, and integrated information requirements for a future technology interface functioning to increase confidence between ground support and LDEM crewmembers.

TRISH↗
DOE OSTI2026

matsim-agents v1.0

matsim-agents is a multi-agent AI framework for atomistic materials simulation and discovery. It orchestrates large language models (LLMs), machine-learned interatomic potentials (MLIPs), and DFT codes into a single agentic loop running on laptops and DOE leadership-class supercomputers. MULTI-AGENT ORCHESTRATION A LangGraph state machine with three nodes: a Planner that converts a natural-language research objective into structured tasks; an Executor that dispatches atomistic tools and loops until the queue is empty; and an Analyst that summarizes results into a human-readable report. State is checkpointed after every step and human-in-the-loop gates can be inserted at any edge. HYPOTHESIS-DRIVEN DISCOVERY CHAT An interactive REPL (matsim-agents chat) that couples LLM dialogue with atomistic simulation. Chemical formulas are automatically detected in conversation turns and trigger a full crystal-phase exploration: structure generation → relaxation → stability scoring → result injection back into the conversation, creating a closed hypothesis-refinement loop. CRYSTAL PHASE ENUMERATION Given a composition, the phase explorer enumerates prototypes by stoichiometry: elemental (fcc/bcc/hcp/sc/diamond), binary 1:1 (rocksalt/CsCl/zincblende/ wurtzite/fluorite/rutile), ternary 1:1:3 (cubic perovskite), ternary 1:2:4 (perovskite + spinel), quaternary 1:1:2:6 (Fm-3m double perovskite). 2-D prototypes (graphene, h-BN, MoS2 2H/1T) and multilayer stacking are also supported via --include-2d and --num-layers. SUPERCELL GENERATION AND SITE DECORATION Auto-tiling to a minimum atom count (--min-atoms), explicit NxNxN tiling (--supercell), symmetry-distinct site decorations (--n-orderings), and isotropic lattice-scale sweeps (--lattice-scales) for volume bracketing. MLFF RELAXATION AND STABILITY SCORING HydraGNN (multi-headed GNN) drives structure relaxation via ASE with FIRE, BFGS, or BFGSLineSearch. Stability output: delta-E/atom ranking across phases and a max-residual-force dynamical-stability proxy. Other MLIPs (MACE, NequIP, Orb) can be plugged in through the same interface. DFT BACKENDS Quantum ESPRESSO pw.x and VASP 6.6 are first-class labellers. Both have validated GPU builds and SLURM/PBS launchers for three DOE platforms: Frontier (AMD MI250X, ROCm), Aurora (Intel PVC, oneAPI), Perlmutter (NVIDIA A100, CUDA). QE produces ~100 binaries (pw.x, ph.x, epw.x, ...). VASP supports scf, relax, vc-relax, and vc-relax-shape run types. ACTIVE-LEARNING LOOP matsim-agents al run CONFIG.yaml drives an iterative HydraGNN-DFT loop: MD generates candidates → ensemble/MC-dropout uncertainty selects the most informative → DFT labels them in parallel inside one allocation → dataset grows → HydraGNN retrains → repeat. DFT backend is a single YAML toggle (dft.backend: vasp | qe). LLM-generated seed structures are supported (no curated POSCAR library needed). Config uses ${VAR}, ${VAR:-default}, ${VAR:?msg} shell-style substitution for cross-user/cross-site portability. LLM BACKENDS Ollama (local, default), vLLM (HPC multi-GPU serving), OpenAI, Anthropic, HuggingFace Transformers+Accelerate. Selected at runtime via flag or env var with no code changes. HPC PORTABILITY Same Python entry points run on Frontier (ROCm 7.2), Aurora (oneAPI), and Perlmutter (CUDA 12). DFT and ML stacks are never co-loaded in the same shell; they couple through the scheduler and filesystem. Advanced multi-node launchers (serve, discovery-chat, single-relaxation, active-learning, QE warm-start) are provided for all three platforms. CODABENCH COMPETITION BUNDLE A self-contained benchmark: 159 atomistic test structures across 11 material classes, 5 tasks (formation energy, forces, ML relaxation, AI-DFT relaxation, phase stability ranking), public/private leaderboard split (30/70), and four ready-to-run baselines: MACE-MP-0, HydraGNN, UMA, AllScAIP.

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗
DOE OSTI2015

Humboldt bay power plant decommissioning transition to civil works - 15039

Decommissioning of the Pacific Gas and Electric (PG and E) Company Humboldt Bay Power Plant (HBPP) Unit 3 nuclear facility has now, after more than three decades of SAFSTOR, completed the Plant Systems Removal Phase by removal of all radiologically significant plant systems from the buildings in June 2014. The HBPP historical design and construction, close proximity to the bay and associated tidal interactions poses unique challenges to an effective decommissioning effort as the Site transitions to a major earthwork project - designated as Civil Works. The last significant large component removal project remaining is segmentation and disposal of the reactor pressure vessel shell and this project is now integrated and executed under Civil Works with PG and E solely in an oversight role across the site beginning 2015. The value from run-up and mock-up testing of tooling to segment the HBPP reactor vessel will be discussed. Experience obtained, especially at error prone interfaces, during start-up, systemisation and operating phases for the First of a Kind (KOAK) tooling will be discussed. Implementation of the civil scope of work commenced July 2013. Its status and experience applicable to other decommissioning efforts will be provided from an owner's perspective. Implementation of the civil work scope includes development and implementation of oversight capability including policy, procedures and deployment of skilled, experienced and trained oversight staff in the field. Challenges encountered and solutions implemented during mobilization and ramp up of the civil contractor commensurate with demobilization of the self-perform staff will be covered. Partnering with the contractor to establish a good Client/Contractor relationship and tips on where to invest owner resources will be shared. Development of a solid baseline project schedule that incorporates regulatory constraints, client expectations and contract constraints and its importance to safe, compliant project execution will be shared. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1989

Space applications of artificial intelligence; Proceedings of the Annual Goddard Conference, Greenbelt, MD, May 16, 17, 1989

Theoretical and implementation aspects of AI systems for space applications are discussed in reviews and reports. Sections are devoted to planning and scheduling, fault isolation and diagnosis, data management, modeling and simulation, and development tools and methods. Particular attention is given to a situated reasoning architecture for space repair and replace tasks, parallel plan execution with self-processing networks, the electrical diagnostics expert system for Spacelab life-sciences experiments, diagnostic tolerance for missing sensor data, the integration of perception and reasoning in fast neural modules, a connectionist model for dynamic control, and applications of fuzzy sets to the development of rule-based expert systems.

Rash, James L.↗
NASA NTRS2005

Design of the Protocol Processor for the ROBUS-2 Communication System

The ROBUS-2 Protocol Processor (RPP) is a custom-designed hardware component implementing the functionality of the ROBUS-2 fault-tolerant communication system. The Reliable Optical Bus (ROBUS) is the core communication system of the Scalable Processor-Independent Design for Enhanced Reliability (SPIDER), a general-purpose fault tolerant integrated modular architecture currently under development at NASA Langley Research Center. ROBUS is a time-division multiple access (TDMA) broadcast communication system with medium access control by means of time-indexed communication schedule. ROBUS-2 is a developmental version of the ROBUS providing guaranteed fault-tolerant services to the attached processing elements (PEs), in the presence of a bounded number of faults. These services include message broadcast (Byzantine Agreement), dynamic communication schedule update, time reference (clock synchronization), and distributed diagnosis (group membership). ROBUS also features fault-tolerant startup and restart capabilities. ROBUS-2 tolerates internal as well as PE faults, and incorporates a dynamic self-reconfiguration capability driven by the internal diagnostic system. ROBUS consists of RPPs connected to each other by a lower-level physical communication network. The RPP has a pipelined architecture and the design is parameterized in the behavioral and structural domains. The design of the RPP enables the bus to achieve a PE-message throughput that approaches the available bandwidth at the physical layer.

Torres-Pomales, Wilfredo↗
DOE OSTI2021

First-principles Prediction of X-Ray Polarization from Magnetic Reconnection in High-frequency BL Lacertae Objects

Relativistic magnetic reconnection is a potential particle acceleration mechanism for high-frequency BL Lac objects (HBLs). The Imaging X-ray Polarimetry Explorer (IXPE) scheduled to launch in 2021 has the capability to probe the evolution of magnetic field in HBLs, examining the magnetic reconnection scenario for the HBL flares. In this paper, we make the first attempt to self-consistently predict HBL X-ray polarization signatures arising from relativistic magnetic reconnection via combined particle-in-cell and polarized radiation transfer simulations. Here, we find that although the intrinsic optical and X-ray polarization degrees are similar on average, the X-ray polarization is much more variable in both the polarization degree and angle (PD and PA). Given the sensitivity of the IXPE, it may obtain one to a few polarization data points for one flaring event of nearby bright HBLs Mrk 421 and 501. However, it may not fully resolve the highly variable X-ray polarization. Due to temporal depolarization, where the integration of photons with variable polarization states over a finite period of time can lower the detected PD, the measured X-ray PD can be considerably lower than the optical counterpart or even undetectable. The lower X-ray PD than the optical thus can be a characteristic signature of relativistic magnetic reconnection. For very bright flares where the X-ray polarization is well resolved, relativistic magnetic reconnection predicts smooth X-ray PA swings, which originate from large plasmoid mergers in the reconnection region.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Scalable, In-situ Data Clustering Data Analysis for Extreme Scale Scientific Computing (Final Report)

The objective of this project is to address challenges in the design and development of scalable in-situ data clustering and analytics algorithms and software. Our goal is to develop parallel software consisting of a set of spatio-temporal data clustering and anomaly detection functions, both of which are very important for large-scale analysis and have wide applicability for in-situ runs as well as post-processing analysis. Our design principles for in-situ analysis consider the following: (1) identify parts of the computation can be done close to the data within the nodes, while it is still in memory; (2) extract analysis components can (and should) be performed in remote staging and analysis nodes; (3) develop error-bound approximation methods for applications tolerable for small errors; (4) identify the type of derived distributions and statistics, for spatio-temporal data, that can be kept locally in order to both accelerate computations and meet energy constraints in subsequent iterations and phases; (5) use a self-describing data format so that data can be consistent and understood among local storage (memory and SSDs) and at staging and analysis nodes, thereby providing portability and flexibility; (6) develop service-oriented functions that can schedule in-situ and post-hoc analysis tasks based on the dynamic requirements of applications. Our development focus is to produce the parallel data analysis software/library that will be scalable, reusable, extensible, and generic for applications in different disciplines. The software will be able to run in-situ with the simulations as well as post-hoc analysis. This approach will satisfy many synergistic requirements for data intensive applications executed on data coming from instruments and experiments. In particular, the proposed multilevel approach is directly applicable to perform design tradeoffs for running part of the algorithms near the instruments and the rest on remote (analysis) systems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1994

Fuzzy self-learning control for magnetic servo system

It is known that an effective control system is the key condition for successful implementation of high-performance magnetic servo systems. Major issues to design such control systems are nonlinearity; unmodeled dynamics, such as secondary effects for copper resistance, stray fields, and saturation; and that disturbance rejection for the load effect reacts directly on the servo system without transmission elements. One typical approach to design control systems under these conditions is a special type of nonlinear feedback called gain scheduling. It accommodates linear regulators whose parameters are changed as a function of operating conditions in a preprogrammed way. In this paper, an on-line learning fuzzy control strategy is proposed. To inherit the wealth of linear control design, the relations between linear feedback and fuzzy logic controllers have been established. The exercise of engineering axioms of linear control design is thus transformed into tuning of appropriate fuzzy parameters. Furthermore, fuzzy logic control brings the domain of candidate control laws from linear into nonlinear, and brings new prospects into design of the local controllers. On the other hand, a self-learning scheme is utilized to automatically tune the fuzzy rule base. It is based on network learning infrastructure; statistical approximation to assign credit; animal learning method to update the reinforcement map with a fast learning rate; and temporal difference predictive scheme to optimize the control laws. Different from supervised and statistical unsupervised learning schemes, the proposed method learns on-line from past experience and information from the process and forms a rule base of an FLC system from randomly assigned initial control rules.

Tarn, J. H.↗
DOE OSTI2019

A Transactive Network Template for Decentralized Coordination of Electricity Provision and Value

Transactive energy systems facilitate and plan for an allocation of electricity based on distributed, value-based negotiations. They are currently extending the usage of market-based principles and transactions from wholesale electricity markets where they exist today downward into distribution systems. While many interesting transactive energy systems have been proposed, few fully decentralize price discovery and price-responsive control. Even fewer plan for extensibility that will be needed for the ultimate growth of transactive networks and for the inclusion of additional and new objectives and new flexible, responsive assets. This paper introduces a transactive network template from which an agent may be configured at its network node to negotiate for electricity with other neighboring network agents, manage a set of locally-owned supply and demand assets, and induce local power balance through price discovery. A set of base object classes defines the template and may be extended. Three important basic computational responsibilities are allocated among the base object classes—scheduling, balancing, and network coordination. These several basic classes and responsibilities may be used to represent the perspective of large and small devices and regions anywhere in the electric power grid because they are based on the self-similarity of these objects and responsibilities. Agents in a transactive network are not at all unique in these basic responsibilities. So far, these following dynamic values have been addressed by extension of the base classes: energy value, demand charges, transport losses, and impacts of distributed renewable resources. The template is designed to be further extended to address and monetize still other valuable objectives.

Transactive, Transactive network, Transactive netw↗
NASA NTRS1989

Earth orbital operations supporting manned interplanetary missions

The orbital operations required to accumulate, assemble, test, verify, maintain, and launch complex manned space systems on interplanetary missions from earth orbit are as vital as the flight hardware itself. Vast numbers of orbital crew are neither necessary nor desirable for accomplishing the required tasks. A suite of robotic techniques under human supervisory control, relying on sensors, software and manipulators either currently emergent or already applied in terrestrial settings, can make the job tractable. The mission vehicle becomes largely self-assembling, using its own rigid aerobrake as a work platform. The Space Station, having been used as a laboratory testbed and to house an assembly crew of four, is not dominated by the process. A feasible development schedule, if begun soon, could emplace orbital support technologies for exploration missions in time for a 2004 first interplanetary launch.

Sherwood, Brent↗
NASA NTRS2015

Integrated Surface Power Strategy for Mars

A National Aeronautics and Space Administration (NASA) study team evaluated surface power needs for a conceptual crewed 500-day Mars mission. This study had four goals: 1. Determine estimated surface power needed to support the reference mission; 2. Explore alternatives to minimize landed power system mass; 3. Explore alternatives to minimize Mars Lander power self-sufficiency burden; and 4. Explore alternatives to minimize power system handling and surface transportation mass. The study team concluded that Mars Ascent Vehicle (MAV) oxygen propellant production drives the overall surface power needed for the reference mission. Switching to multiple, small Kilopower fission systems can potentially save four to eight metric tons of landed mass, as compared to a single, large Fission Surface Power (FSP) concept. Breaking the power system up into modular packages creates new operational opportunities, with benefits ranging from reduced lander self-sufficiency for power, to extending the exploration distance from a single landing site. Although a large FSP trades well for operational complexity, a modular approach potentially allows Program Managers more flexibility to absorb late mission changes with less schedule or mass risk, better supports small precursor missions, and allows a program to slowly build up mission capability over time. A number of Kilopower disadvantages-and mitigation strategies-were also explored.

Rucker, Michelle↗