Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “battery failure modeling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

89 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

A Fast Monte Carlo Method for Model-Based Prognostics Based on Stochastic Calculus

This work proposes a fast Monte Carlo method to solve differential equations utilized in model-based prognostics. The methodology is derived from the theory of stochastic calculus, and the goal of such a method is to speed up the estimation of the probability density functions describing the independent variable evolution over time. In the prognostic scenarios presented in this paper, the stochastic differential equations describe variables directly or indirectly related to the degradation of a monitored system. The method allows the estimation of the probability density functions by solving the deterministic equation and approximating the stochastic integrals using samples of the model noise. By so doing, the prognostic problem is solved without the Monte Carlo simulation based on Euler's forward method, which is typically the most time consuming task of the prediction stage. Three different prognostic scenarios are presented as proof of concept: (i) life prediction of electrolytic capacitors, (ii) remaining time to discharge of Lithium-ion batteries, and (iii) prognostic of cracked structures under fatigue loading. The paper shows how the method produces probability density functions that are statistically indistinguishable from the distributions estimated with Euler's forward Monte Carlo simulation. However, the proposed solution is orders of magnitude faster when computing the time-to-failure distribution of the monitored system. The approach may enable complex real-time prognostics and health management solutions with limited computing power.

Corbetta, M.↗
NASA NTRS2019

A Fast Monte Carlo Method for Model-Based Prognostics Based on Stochastic Calculus

This work proposes a fast Monte Carlo method to solve differential equations utilized in model-based prognostics. The methodology is derived from the theory of stochastic calculus, and the goal of such a method is to speed up the estimation of the probability density functions describing the independent variable evolution over time. In the prognostic scenarios presented in this paper, the stochastic differential equations describe variables directly or indirectly related to the degradation of a monitored system. The method allows the estimation of the probability density functions by solving the deterministic equation and approximating the stochastic integrals using samples of the model noise. By so doing, the prognostic problem is solved without the Monte Carlo simulation based on Euler's forward method, which is typically the most time consuming task of the prediction stage. Three different prognostic scenarios are presented as proof of concept: (i) life prediction of electrolytic capacitors, (ii) remaining time to discharge of Lithium-ion batteries, and (iii) prognostic of cracked structures under fatigue loading. The paper shows how the method produces probability density functions that are statistically indistinguishable from the distributions estimated with Euler's forward Monte Carlo simulation. However, the proposed solution is orders of magnitude faster when computing the time-to-failure distribution of the monitored system. The approach may enable complex real-time prognostics and health management solutions with limited computing power.

stochastic calculus↗
NASA NTRS2017

Physics-of-Failure Approach to Prognostics

As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in accurate prediction of the electrical components present in the system. In case of electric vehicles, computing remaining battery charge is safety-critical. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle. In this presentation our approach to develop a system level health monitoring safety indicator for different electronic components is presented which runs estimation and prediction algorithms to determine state-of-charge and estimate remaining useful life of respective components. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making.

Kulkarni, Chetan S.↗
NASA NTRS1999

Nondestructive Evaluation Correlated with Finite Element Analysis

Advanced materials are being developed for use in high-temperature gas turbine applications. For these new materials to be fully utilized, their deformation properties, their nondestructive evaluation (NDE) quality and material durability, and their creep and fatigue fracture characteristics need to be determined by suitable experiments. The experimental findings must be analyzed, characterized, modeled and translated into constitutive equations for stress analysis and life prediction. Only when these ingredients - together with the appropriate computational tools - are available, can durability analysis be performed in the design stage, long before the component is built. One of the many structural components being evaluated by the NDE group at the NASA Lewis Research Center is the flywheel system. It is being considered as an energy storage device for advanced space vehicles. Such devices offer advantages over electrochemical batteries in situations demanding high power delivery and high energy storage per unit weight. In addition, flywheels have potentially higher efficiency and longer lifetimes with proper motor-generator and rotor design. Flywheels made of fiber-reinforced polymer composite material show great promise for energy applications because of the high energy and power densities that they can achieve along with a burst failure mode that is relatively benign in comparison to those of flywheels made of metallic materials Therefore, to help improve durability and reduce structural uncertainties, we are developing a comprehensive analytical approach to predict the reliability and life of these components under these harsh loading conditions. The combination of NDE and two- and three-dimensional finite element analyses (e.g., stress analyses and fracture mechanics) is expected to set a standardized procedure to accurately assess the applicability of using various composite materials to design a suitable rotor/flywheel assembly.

Abdul-Azid, Ali↗
DOE OSTI2026

Predicting Li-Ion Battery Capacity Fade Using Early-Life Data and a Hybrid Data-Driven Gaussian Process-Bayesian Regression Approach

Accurately predicting Li-ion battery capacity trajectories using early-life data can dramatically improve battery-life understandings and be used to rapidly evaluate design/cost/performance trade-offs when developing new battery materials. Accurate early-life predictions enable researchers to quickly iterate over cell designs and material precursor properties without consistently cycling cells to failure. To this end, we present a toolbox that uses a combined Gaussian Process and Bayesian regression approach that capitalizes on signals other than just capacity (e.g., dQ/dV, voltage drops) to rapidly predict capacity-fade trajectories. The prediction tool uses Bayesian regression to fit functional forms, e.g., power law, sigmoids, etc., to predict capacity-fade dynamics. By fitting functional forms, the capacity fade can be interrogated at any point in the future, allowing for early cell-failure prediction. Additionally, Bayesian regression allows for accurate uncertainty estimates that account for cell-to-cell variability (aleatoric uncertainty) and the lack of observation data (epistemic uncertainty). By only using early cycle data to predict the capacity fade trajectory, uncertainty bounds at end-of-life can be extremely large. The large uncertainty bounds are further exacerbated because there is no systematic way to define the prior distribution of the functional forms' parameters. We improve our the predicted trajectory confidence interval of our predicted trajectory using two methods. First, we shows that a small amount of held-out cycling data is sufficientuse some train cells, that have been cycled to failure to derive information regarding the appropriate prior distributions for the functional forms' parameters of the functional form, effectively leading to data-driven priors.. We propose constructing the data-driven priors by first running a Bayesian regression starting with uninformed priors to generate intermediate cell-specific posterior parameter distributions. These posterior distributions are combined using a Ggaussian mixture model for each parameter to create the data-driven priors. These mixture models serve as the data-driven prior distributions for the parameters for. Second, we derive multiple features, e.g., C_dchg 0.5 DoD 0.5, log (|mean(dQ/dV_(w_3-w_0 ) (V)|), etc., from the train cellsheld-out cycling data, identify which the features are that best predicting capacity at early/mid-life cycles, and then create Ggaussian process regression models that are used for predicting capacity at early/mid-life cycles for the test cells (see blue dots with error bars in Fig 1b). Finally, these predicted data-points are used in addition to the actual early cycle data capacity fade to construct the Bayesian regression trajectory for the test cell s. Notably. We note that these two methods are complementary and can be combined with each other. We evaluate the performance of our proposed method on an testing open-source dataset from Iowa State University and Iowa Lakes Community College (ISU-ILCC). This dataset comprises of 251 nickel-manganese-cobalt/graphite Lithium-ion cells that are cycled under 63 different conditions. We compute the mean average percentage error (MAPE) and negative log predictive density (NLPD) to quantify the efficacy of our method. Our initial findings suggest that, when only few observations are available, for test cells, when using only Bayesian regression with uninformed priors, a power law functional provides the most accurate predictions. with very few data points. However, asHowever, a the number of data points increases, a twin sigmoidal function becomes more accurate as the number of observations further increases. We also find that using as little as 10% of the data set towards generating data-driven priors can lead to significant improvement in prediction accuracy when using early cycle data. Lastly, we found that augmenting early-cycle data with Gaussian process-predicted capacity data for Bayesian regression greatly improves the prediction accuracy. We will present a comprehensive comparison of our methods to other methods available in the literature and apply this method to additional battery datasets.

42 ENGINEERING↗
DOE OSTI2026

White Paper on Case Study of Safe Installation of Second-Life Energy Storage System

This technical report provides for a case study for the safe installation of a second-life, or repurposed, battery, that has been reconfigured for use as a stationary energy storage systems (ESS). Driven by legislative requirements such as California Senate Bill 615 and projections that retired EV batteries could meet a substantial portion of U.S. grid ESS needs beginning in 2035, the repurposing of EV batteries is anticipated to grow significantly. However, safety concerns arise from the effects of aging, unknown prior usage history, and changes in thermal runaway behavior, which may increase failure risks compared to new batteries. NFPA 855, the predominant U.S. standard for ESS installation, mandates that second-life batteries meet all requirements for new batteries, with repurposers complying with UL 1974 in addition to obtaining UL 9540 and UL 1973 listings. These are certifications that few repurposers have achieved and represent a regulatory barrier to entry for the market as a whole.

47 OTHER INSTRUMENTATION↗
NASA NTRSDate not supplied

Simulation Studies for an Urban Air Mobility Aircraft using Hardware-In-Loop Experiments

Urban Air Mobility seeks to transport passengers, deliver cargo, and provide emergency transportation in major metropolitan areas. This will be accomplished with distributed electric-powered vertical takeoff and landing aircraft. The low specific energy of the current generation lithium-ion battery packs limit the operational range of electric aircraft. Limited range impacts safety by reducing the time available for analyzing and responding to errors and failures, and limiting the ability to fly to an alternative landing area or return to base. It is therefore critical to understand flight operational and environmental conditions that impact the onboard lithium-ion polymer battery pack’s health. With this as the motivation, experimental procedure in a laboratory setting, and results of the experiments performed on battery packs subject to power draw corresponding to power required during the different phases of flight of a NASA conceptual quadrotor aircraft in simulation are described. The fully charged battery is allowed to discharge at specific C-rates based on the power draw profile and the current and voltages are recorded. Observed results under different operating conditions and mission profiles are discussed.

UAM↗
DOE OSTI2024

LogPath: Log data based energy consumption analysis enabling electric vehicle path optimization

Vehicle navigation and path optimization require a more meticulous approach when it deals with EVs (electric vehicles) and SDVs (software-defined vehicles), due to lengthy charging times and the lack of charging infrastructure. Long-distance freight EV trucking needs path guidance with accurate energy consumption estimates to prevent charging-related failures. We developed a novel energy consumption estimation approach that only uses battery log data to extract major vehicle parameters to increase EV navigation accuracy without additional sensors. This is enabled by extracting multiple drive modes from the log data for analysis. The system provides 1) routes, 2) charge locations, 3) charging times, and 4) optimal vehicle speeds that guarantee the shortest travel time. Here we successfully validated the system using log data collected from an EV and Tesla's Supercharging map in the US and compared it with the commercially available navigation system, Tesla's trip planner, whose capabilities solely include charging time and routing.

EV (Electric vehicles) navigation↗
NASA NTRS2012

Real-Time Projection to Verify Plan Success During Execution

The Mission Data System provides a framework for modeling complex systems in terms of system behaviors and goals that express intent. Complex activity plans can be represented as goal networks that express the coordination of goals on different state variables of the system. Real-time projection extends the ability of this system to verify plan achievability (all goals can be satisfied over the entire plan) into the execution domain so that the system is able to continuously re-verify a plan as it is executed, and as the states of the system change in response to goals and the environment. Previous versions were able to detect and respond to goal violations when they actually occur during execution. This new capability enables the prediction of future goal failures; specifically, goals that were previously found to be achievable but are no longer achievable due to unanticipated faults or environmental conditions. Early detection of such situations enables operators or an autonomous fault response capability to deal with the problem at a point that maximizes the available options. For example, this system has been applied to the problem of managing battery energy on a lunar rover as it is used to explore the Moon. Astronauts drive the rover to waypoints and conduct science observations according to a plan that is scheduled and verified to be achievable with the energy resources available. As the astronauts execute this plan, the system uses this new capability to continuously re-verify the plan as energy is consumed to ensure that the battery will never be depleted below safe levels across the entire plan.

Wagner, David A.↗
NASA NTRS2019

Characterization of Laptop Fires in Spacecraft

An accidental fire involving the Lithium-Ion (Li-ion) battery in a laptop computer is one of the most likely fire scenarios on-board a spacecraft. These fires can occur from a defect in the battery that worsens with time, over-charging the battery and leading to failure or accidental damage caused by thermal runaway. While this is a relatively likely fire scenario, very little is known about the how a laptop computer fire would impact a sealed spacecraft. The heat release would likely cause a pressure rise, possibly exceeding the pressure limit of the vehicle and causing a relief valve to open. The combustion products from the fire could pose a short-term and long-term health hazard to the crew and the fire itself could cause injury to the crew and damage to the spacecraft. Despite the hazard posed by a laptop fire, there is little quantitative data on the fire size, heat release and toxic product formation. This paper presents the results of initial attempts to quantify the fire resulting from a failed laptop fire tested at the NASA White Sands Test Facility (WSTF). The data from the testing is useful to attempt to determine the fire size and characteristics such as maximum heat release rate, total heat release, maximum temperatures and fire duration are determined. Using existing models and correlations for fires, the measured fire characteristics are extrapolated to laptop fires on a vehicle the approximate size of the Orion spacecraft.

Padilla, Rosa E.↗
NASA NTRS2021

Local Ultrasonic Resonance Spectroscopy of Lithium Metal Batteries for Aerospace Applications

As next-generation aircraft and vehicles continue to develop, so do their associated energy demands. Lithium metal batteries are a leading candidate to fulfill this energy requirement, but these batteries are prone to internal dendrite defects that can lead to catastrophic thermal runaway events. Current battery management systems are capable of mitigating such risks, but are unable to detect such defects until thermal runaway has already begun. Various nondestructive evaluation (NDE) techniques, particularly ultrasonic NDE, can directly monitor internal battery parameters giving them the potential to detect critical defects prior to catastrophic failure. However, most of the current battery NDE research has focused on improved battery state-of-charge (SOC) and stateof- health (SOH) monitoring with little emphasis on critical defect detection. Thus, a measurement technique sensitive to subtle battery defects is needed. In addition, the complex mechanics of ultrasound in porous, thin, multilayered batteries prompt the use of physics-based simulation to guide inspections. In this work, an ultrasonic NDE technique has been developed utilizing frequency domain analysis of local battery resonances to detect the presence of battery defects. This technique is a practical extension of local ultrasonic resonance spectroscopy (LURS) – which previously required non-contact laser ultrasonics – to measurements with piezoelectric contact and immersion scan transducers. To extend the technique to work with piezoelectric transducers, ultrasonic battery measurements were compared to a sans-battery calibration measurement. Then, a linear systems deconvolution was used to eliminate the transfer functions of extraneous factors such as the transducer and electronics, leaving only the frequency-dependent battery reflection coefficient. The LURS technique was first validated on stainless steel and aluminum plates, producing reflection coefficients in line with analytical and numerical finite element modeling (FEM) results. Functioning Li-metal pouch cells were then seeded with lithium chip defects prior to LURS measurements. The presence of these defects is shown to cause a measurable shift in the battery’s through-thickness local resonances. 2D, frequency-domain poroelastic models of ultrasonic propagation in a single-cell lithium metal pouch battery were created and corroborated these findings. Thus, this work has both extended and proven the feasibility of the LURS technique in the detection of local battery defects.

Ultrasound↗
DOE OSTI2024

Probing degradation at solid-state battery interfaces using machine-learning interatomic potential

Solid-state batteries featuring fast ion-conducting solid electrolytes are promising next-generation energy storage technologies, yet challenges remain for practical deployment due to electro-chemo-mechanical instabilities at solid-solid interfaces. These interfaces, which include homogeneous/internal interfaces such as grain boundaries (GBs) and heterogeneous/external interfaces between solid-electrolyte and electrode materials, can impede Li-ion transport, deteriorate performance, and eventually lead to cell failure. Here, in this study, we leverage large-scale molecular simulations, enabled by validated machine-learning interatomic potentials, to directly probe the onset of interfacial degradation at the garnet Li 7 La 3 Zr 2 O 12 (LLZO) solid-electrolyte/LiCoO 2 (LCO) cathode interface. By surveying different interfacial geometries and compositions, it is found that Li-deficient interfaces can lead to severe interfacial disordering with cation mixing and Co interdiffusion from LCO into LLZO. By contrast, Li-sufficient interfaces are less disordered, although elemental segregation with local ordering is observed. As a consequence of Co interdiffusion, Co-rich regions are formed at the GBs of LLZO due to cation segregation and trapping effects. This behavior is independent of the GB tilting axis, degree of disorder at the GBs, and Co concentration, which implies Co clustering at GBs is a general phenomenon in polycrystalline LLZO and can dictate its overall transport and mechanical properties. Our findings elucidate the underlying fundamental mechanisms that give rise to experimentally observed physicochemical properties and provide guidelines for interface design that can mitigate interfacial degradation and improve cycling performance.

25 ENERGY STORAGE↗
DOE OSTI2025

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

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

Energy constraints↗
NASA NTRS2019

Constraint-Based Off-Nominal Behavior Modeling for Europa Clipper

The risk analysis for the Europa Clipper mission evaluates the probability of mission failure based on the failure rates of individual components and dependencies among them. The probabilities are calculated by integrating over the intervals of time within which a fault occurs, accounting for an infinite number of cases. The response of the spacecraft to different faults can result in different schedules of activities, changing the intervals of integration. Europa currently uses models of spacecraft systems and components to simulate individual flight scenarios. The goal is to develop a framework for integrating, automating, and improving this modeling process. We describe an approach to generating the schedules for the different fault cases and determining the intervals for faults. It is not enough to just simulate individual cases because we are working with continuous variables that generate an infinite number of possible futures. Instead, we determine time windows within which certain faults can occur and use these time windows as bounds for integration. We found that determining these time windows is a constraint optimization problem. In order to represent these problems, we employ a language based on ontologies of behavior and scenarios. The language enables us to specify constraints in a simple, declarative syntax. A constraint-based analysis engine uses the declarative specification to identify bounds on system parameters and fill in details of behavior. For example, we created a detailed model of power generation, power use, and the corresponding effects on the battery in order to determine when an undervoltage fault can occur. An undervoltage during a trajectory correction maneuver requires that thrusting be interrupted for just enough time to recharge the battery such that the maneuver can be completed within battery limits. This behavior is generated based on the model to minimize the interruption time. For certain scenarios the constraint optimization problems were simple enough to be solved by hand, but the framework made the process substantially faster. It also produced solutions to other problems that we could not solve by hand or with existing tools and allowed us to generate and run many scenarios at once. The scenario language and engine greatly simplified the process of identifying time bounds and separating cases.

Everline, Chester J.↗
DOE OSTI2025

Enhancing building resilience in cold climates: Integrating heat pump technologies with renewable energy

As electrification advances and Cold Climate Heat Pump technology progresses, ensuring grid stability becomes increasingly critical for effective heating in cold climates. However, natural disasters, especially during winter, pose significant threats to grid stability, impacting the reliability of air-source heat pumps. Despite these challenges, the integration of renewable energy sources and storage solutions in heating systems has not been extensively studied within the context of resilience. Here, this paper delves into the literature on renewable-powered heat pumps to assess their potential in enhancing building resilience in U.S. cold climate zones, which are particularly susceptible to extreme weather and grid disruptions. By leveraging renewable sources—solar, geothermal, and water—in conjunction with heat pump technology and supported by thermal or battery storage, this approach aims to provide a dependable solution for maintaining indoor heating during grid failures. Our analysis begins with a review of various renewable energy sources suitable for heat pumps, followed by an exploration of their application in cold climate regions across the U.S., and discussions on potential integration strategies with heat pump systems. This study highlights the advantages and suitability of solar irradiance and geothermal resources, emphasizing the importance of tailored, site-specific assessments to maximize energy efficiency and resilience. Additionally, it outlines the economic and environmental considerations necessary for implementing such systems and identifies potential challenges and areas for future research to facilitate the broader integration of renewable energy in heating solutions for enhanced resilience.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

NASA's Habitation Development Status: Current Concepts and ISRU Opportunities

Introduction: The National Aeronautics and Space Administration (NASA) is embarking on a bold journey to return humankind to the Moon and onward to Mars with innovative commercial, international, and academic partnerships. Under the Artemis series of missions, NASA seeks to establish sustained human exploration of deep space through an objectives-based approach. This approach drives the identification of needed system functionality and the current and future capabilities which will eventually allow humanity to sustainably live beyond Earth. Providing evolvable and scalable habitation is a cornerstone function that calls for the collection and integration of current, developmental, and future technologies that can meet near-term exploration needs while growing into long-term sustained presence. NASA is advancing in-space habitation through its Next Space Technologies for Exploration Partnerships (NextSTEP) model while designing lunar, Mars transit, and Mars surface habitat government reference concepts for Artemis missions. These efforts have unveiled possible near-term opportunities for the in-space resource utilization community if human habitation is considered a future customer of space resources. NextSTEP Habitation Development: NASA is closely working with commercial partners under its NextSTEP Appendix A model to advance habitation systems in the arena of inflatable and composite habitation structures. Such efforts promise efficiencies in volumetric packaging and overall spacecraft mass respectively. Recent testing by commercial partners have helped to quantify possible failure mechanisms for inflatable structures while advancing their technology towards eventual flight certification. The advancement of such Class II habitation structures, in which the habitat is only fully deployed once in-space or on a planetary surface, is critical to providing increased habitable volume for long-duration missions with no additional mass penalties. The progression of such technology is infused into NASA’s government reference concepts for notional deep space habitation concepts. Current Government Reference Concepts: To best inform the formulation of future collaborative solicitations, NASA employs the practice of internally developing reference concepts for future exploration elements. These concepts aid in identifying the functions and capabilities needed to complete NASA missions as well as feasible solutions within the timeframe needed. Government reference concepts for a lunar Surface Habitat, Mars Transit Habitat, and Mars Sur-face Habitat are continuously being developed and updated to better guide the Agency’s overall exploration architecture. Lunar Surface Habitat. As NASA returns to the Moon, it is evaluating possible lunar surface habitation concepts. The Surface Habitat (SH) reference concept entails a hybrid metallic-inflatable structure capable of initially housing two crew for surface stays of up to 30 days in duration. While initial missions may span ~7 days in duration, consideration is being given to expanding SH’s capability to support a crew of four for up to 60 days over its 15-year design life. Functionally, the SH serves as a ‘hub’ for all Artemis crewed surface operations, providing internal volume for maintenance, medical, logistics, science utilization, and extravehicular activity (EVA) support in addition to core habitation functionality such as environmental control and life support (ECLS) and power generation and distribution among many others. Additionally, NASA has entered a study agreement with the Italian Space Agency (Agenzia Spaziale Italiana – ASI) to investigation a possible Multi-Purpose Habitat (MPH) as an additional or augmenting habit-able element for the lunar surface. Mars Transit Habitat. NASA’s current architectural concept for initial human missions to Mars entails the utilization of a transit habitat (TH) to transport a four-person crew to and from Mars orbit, departing from and returning to a lunar near-rectilinear halo orbit (NRHO), over the course of a ~1,200-day mission. While holding a similar 15-year design lifetime, TH will also support a series of analog mission activities in NRHO to gradually test the systems and interaction with lunar surface elements, some of which may be adapted for Mars surface exploration. Holding similar functional capabilities as SH, TH is sized to support much longer durations in space and greater logistical independence. Mars Surface Habitat. NASA is still exploring the concept of operations for initial crewed missions to Mars. As such, the Mars Surface Habitat (MSH) concept is still in its infancy as options for mobile, pressurized habitation and stationary habitats are being explored. It is expected MSH will leverage heavily from the lunar SH and possible lunar pressurized rover, however the very different Martian environment will likely necessitate modifications. ISRU Opportunities: Despite the advancements under NASA’s NextSTEP habitation work and continually optimized reference concepts, NASA is facing near-term mass and power challenges that may create opportunities to the ISRU community by providing yet another possible customer for space resources. While NASA desires to use regenerative ECLS systems (ECLSS) for all habitation concepts, their operation comes with initial mass penalties and maintenance overheads when compared to simpler open-loop architectures. Because of this, NASA is currently pro-posing an open-loop, consumables-based architecture for its surface habitats to achieve initial launch and delivery lander mass targets while scarring for the in-corporation of regenerative ECLSS to meet longer mission durations and sustained presence. With such an architecture, oxygen and potable water are needed consumables, which initial ISRU systems may be able to provide in a pilot capacity. Although the TH is expecting to utilize regenerative ECLSS, advancements in lunar surface-based ISRU and possible re-supply of spacecraft in lunar or Mars orbit could significantly reduce the logistical need for ECLSS related spares on TH and possibly allow a similar open-loop and consumables-based architecture. In addition to ECLSS mass concerns, the SH is facing challenges with energy storage to support operations over periods of darkness exceeding 100 hours. Both battery and fuel cell-based power architectures are being traded, opening options for external power generation and energy storage. One possibility is ISRU-produced H2 and O2 feeding external primary fuel cell systems which could supplement habitation power generation while reducing initial mass and volume until much more powerful fission power systems might be deployed. Conclusion: Significant advancements are being made in evolvable habitation concepts that span from near-term technologies, such as inflatable structures under NextSTEP, to potentially revolutionary capabilities like the lunar surface construction as funded through the Moon-to-Mars Planetary Autonomous Construction Technologies (MMPACT) project. As NASA investigates both heritage capabilities and rap-idly advancing, disruptive technologies, there are likely many near-term opportunities for initial ISRU capabilities to significantly aid human habitation and increase self-sufficiency beyond Earth.

habitation↗
NASA NTRSDate not supplied

NASA's Habitation Development Status: Current Concepts and ISRU Opportunities

Introduction: The National Aeronautics and Space Administration (NASA) is embarking on a bold journey to return humankind to the Moon and onward to Mars with innovative commercial, international, and academic partnerships [1]. Under the Artemis series of missions, NASA seeks to establish sustained human exploration of deep space through an objectives-based approach [2]. This approach drives the identification of needed system functionality and the current and future capabilities which will eventually allow humanity to sustainably live beyond Earth. Providing evolvable and scalable habitation is a cornerstone function that calls for the collection and integration of current, developmental, and future technologies that can meet near-term exploration needs while growing into long-term sustained presence. NASA is advancing in-space habitation through its Next Space Technologies for Exploration Partnerships (NextSTEP) model while designing lunar, Mars transit, and Mars surface habitat government reference concepts for Artemis missions. These efforts have unveiled possible near-term opportunities for the in-space resource utilization community if human habitation is considered a future customer of space resources. NextSTEP Habitation Development: NASA is closely working with commercial partners under its NextSTEP Appendix A model to advance habitation systems in the arena of inflatable and composite habitation structures. Such efforts promise efficiencies in volumetric packaging and overall spacecraft mass respectively. Recent testing by commercial partners have helped to quantify possible failure mechanisms for inflatable structures while advancing their technology towards eventual flight certification. The advancement of such Class II habitation structures, in which the habitat is only fully deployed once in-space or on a planetary surface [3], is critical to providing increased habitable volume for long-duration missions with no additional mass penalties. The progression of such technology is infused into NASA’s government reference concepts for notional deep space habitation concepts. Current Government Reference Concepts: To best inform the formulation of future collaborative solicitations, NASA employs the practice of internally developing reference concepts for future exploration elements. These concepts aid in identifying the functions and capabilities needed to complete NASA missions as well as feasible solutions within the timeframe needed. Government reference concepts for a lunar Surface Habitat, Mars Transit Habitat, and Mars Sur-face Habitat are continuously being developed and updated to better guide the Agency’s overall exploration architecture. Lunar Surface Habitat. As NASA returns to the Moon, it is evaluating possible lunar surface habitation concepts. The Surface Habitat (SH) reference concept entails a hybrid metallic-inflatable structure capable of initially housing two crew for surface stays of up to 30 days in duration [4]. While initial missions may span ~7 days in duration, consideration is being given to expanding SH’s capability to support a crew of four for up to 60 days over its 15-year design life [5]. Functionally, the SH serves as a ‘hub’ for all Artemis crewed surface operations, providing internal volume for maintenance, medical, logistics, science utilization, and extravehicular activity (EVA) support in addition to core habitation functionality such as environmental control and life support (ECLS) and power generation and distribution among many others. Additionally, NASA has entered a study agreement with the Italian Space Agency (Agenzia Spaziale Italiana – ASI) to investigation a possible Multi-Purpose Habitat (MPH) as an additional or augmenting habit-able element for the lunar surface [6]. Mars Transit Habitat. NASA’s current architectural concept for initial human missions to Mars entails the utilization of a transit habitat (TH) to transport a four-person crew to and from Mars orbit, departing from and returning to a lunar near-rectilinear halo orbit (NRHO), over the course of a ~1,200-day mission [5]. While holding a similar 15-year design lifetime, TH will also support a series of analog mission activities in NRHO to gradually test the systems and interaction with lunar surface elements, some of which may be adapted for Mars surface exploration. Holding similar functional capabilities as SH, TH is sized to support much longer durations in space and greater logistical independence. Mars Surface Habitat. NASA is still exploring the concept of operations for initial crewed missions to Mars. As such, the Mars Surface Habitat (MSH) concept is still in its infancy as options for mobile, pressurized habitation and stationary habitats are being explored. It is expected MSH will leverage heavily from the lunar SH and possible lunar pressurized rover, however the very different Martian environment will likely necessitate modifications. ISRU Opportunities: Despite the advancements under NASA’s NextSTEP habitation work and continually optimized reference concepts, NASA is facing near-term mass and power challenges that may create opportunities to the ISRU community by providing yet another possible customer for space resources. While NASA desires to use regenerative ECLS systems (ECLSS) for all habitation concepts, their operation comes with initial mass penalties and maintenance overheads when compared to simpler open-loop architectures. Because of this, NASA is currently pro-posing an open-loop, consumables-based architecture for its surface habitats to achieve initial launch and delivery lander mass targets while scarring for the in-corporation of regenerative ECLSS to meet longer mission durations and sustained presence. With such an architecture, oxygen and potable water are needed consumables, which initial ISRU systems may be able to provide in a pilot capacity. Although the TH is expecting to utilize regenerative ECLSS, advancements in lunar surface-based ISRU and possible re-supply of spacecraft in lunar or Mars orbit could significantly reduce the logistical need for ECLSS related spares on TH and possibly allow a similar open-loop and consumables-based architecture. Table 1 Notional ECLSS consumables per mission use for SH and TH [5]. SH (28-day) Open Loop: Water (kg) 288 | Oxygen (kg) 30 TH (1110-day) Closed-Loop: Water (kg) 182 | Oxygen (kg) 123 In addition to ECLSS mass concerns, the SH is facing challenges with energy storage to support operations over periods of darkness exceeding 100 hours. Both battery and fuel cell-based power architectures are being traded, opening options for external power generation and energy storage. One possibility is ISRU-produced H2 and O2 feeding external primary fuel cell systems which could supplement habitation power generation while reducing initial mass and volume until much more powerful fission power systems might be deployed. Conclusion: Significant advancements are being made in evolvable habitation concepts that span from near-term technologies, such as inflatable structures under NextSTEP, to potentially revolutionary capabilities like the lunar surface construction as funded through the Moon-to-Mars Planetary Autonomous Construction Technologies (MMPACT) project [7]. As NASA investigates both heritage capabilities and rap-idly advancing, disruptive technologies, there are likely many near-term opportunities for initial ISRU capabilities to significantly aid human habitation and increase self-sufficiency beyond Earth.

habitation↗