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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Explosion/Blast Dynamics for Constellation Launch Vehicles Assessment

An assessment methodology is developed to guide quantitative predictions of adverse physical environments and the subsequent effects on the Ares-1 crew launch vehicle associated with the loss of containment of cryogenic liquid propellants from the upper stage during ascent. Development of the methodology is led by a team at Sandia National Laboratories (SNL) with guidance and support from a number of National Aeronautics and Space Administration (NASA) personnel. The methodology is based on the current Ares-1 design and feasible accident scenarios. These scenarios address containment failure from debris impact or structural response to pressure or blast loading from an external source. Once containment is breached, the envisioned assessment methodology includes predictions for the sequence of physical processes stemming from cryogenic tank failure. The investigative techniques, analysis paths, and numerical simulations that comprise the proposed methodology are summarized and appropriate simulation software is identified in this report.

Baer, Mel↗
NASA NTRS2001

Hybrid Modeling for Scenario-Based Evaluation of Failure Effects in Advanced Hardware-Software Designs

This paper describes an incremental scenario-based simulation approach to evaluation of intelligent software for control and management of hardware systems. A hybrid continuous/discrete event simulation of the hardware dynamically interacts with the intelligent software in operations scenarios. Embedded anomalous conditions and failures in simulated hardware can lead to emergent software behavior and identification of missing or faulty software or hardware requirements. An approach is described for extending simulation-based automated incremental failure modes and effects analysis, to support concurrent evaluation of intelligent software and the hardware controlled by the software

Malin, Jane T.↗
NASA NTRS2011

Design, Optimization and Evaluation of Integrally Stiffened Al 7050 Panel with Curved Stiffeners

A curvilinear stiffened panel was designed, manufactured, and tested in the Combined Load Test Fixture at NASA Langley Research Center. The panel was optimized for minimum mass subjected to constraints on buckling load, yielding, and crippling or local stiffener failure using a new analysis tool named EBF3PanelOpt. The panel was designed for a combined compression-shear loading configuration that is a realistic load case for a typical aircraft wing panel. The panel was loaded beyond buckling and strains and out-of-plane displacements were measured. The experimental data were compared with the strains and out-of-plane deflections from a high fidelity nonlinear finite element analysis and linear elastic finite element analysis of the panel/test-fixture assembly. The numerical results indicated that the panel buckled at the linearly elastic buckling eigenvalue predicted for the panel/test-fixture assembly. The experimental strains prior to buckling compared well with both the linear and nonlinear finite element model.

Slemp, Wesley C. H.↗
NASA NTRS2011

Reusable Solid Rocket Motor - Accomplishments, Lessons, and a Culture of Success

The Reusable Solid Rocket Motor represents the largest solid rocket motor ever flown and the only human rated solid motor. Each Reusable Solid Rocket Motor (RSRM) provides approximately 3-million lb of thrust to lift the integrated Space Shuttle vehicle from the launch pad. The motors burn out approximately 2 minutes later, separate from the vehicle and are recovered and refurbished. The size of the motor and the need for high reliability were challenges. Thrust shaping, via shaping of the propellant grain, was needed to limit structural loads during ascent. The motor design evolved through several block upgrades to increase performance and to increase safety and reliability. A major redesign occurred after STS-51L with the Redesigned Solid Rocket Motor. Significant improvements in the joint sealing systems were added. Design improvements continued throughout the Program via block changes with a number of innovations including development of low temperature o-ring materials and incorporation of a unique carbon fiber rope thermal barrier material. Recovery of the motors and post flight inspection improved understanding of hardware performance, and led to key design improvements. Because of the multidecade program duration material obsolescence was addressed, and requalification of materials and vendors was sometimes needed. Thermal protection systems and ablatives were used to protect the motor cases and nozzle structures. Significant understanding of design and manufacturing features of the ablatives was developed during the program resulting in optimization of design features and processing parameters. The project advanced technology in eliminating ozone-depleting materials in manufacturing processes and the development of an asbestos-free case insulation. Manufacturing processes for the large motor components were unique and safety in the manufacturing environment was a special concern. Transportation and handling approaches were also needed for the large hardware segments. The reusable solid rocket motor achieved significant reliability via process control, ground test programs, and postflight assessment. Process control is mandatory for a solid rocket motor as an acceptance test of the delivered product is not feasible. Process control included process failure modes and effects analysis, statistical process control, witness panels, and process product integrity audits. Material controls and inspections were maintained throughout the sub tier vendors. Material fingerprinting was employed to assess any drift in delivered material properties. The RSRM maintained both full scale and sub-scale test articles. These enabled continuous improvement of design and evaluation of process control and material behavior. Additionally RSRM reliability was achieved through attention to detail in post flight assessment to observe any shift in performance. The postflight analysis and inspections provided invaluable reliability data as it enables observation of actual flight performance, most of which would not be available if the motors were not recovered. These unique challenges, features of the reusable solid rocket motor, materials and manufacturing issues, and design improvements will be discussed in the paper.

Moore, Dennis R.↗
NASA NTRS2012

Design, Optimization, and Evaluation of A1-2139 Compression Panel with Integral T-Stiffeners

A T-stiffened panel was designed and optimized for minimum mass subjected to constraints on buckling load, yielding, and crippling or local stiffener failure using a new analysis and design tool named EBF3PanelOpt. The panel was designed for a compression loading configuration, a realistic load case for a typical aircraft skin-stiffened panel. The panel was integrally machined from 2139 aluminum alloy plate and was tested in compression. The panel was loaded beyond buckling and strains and out-of-plane displacements were extracted from 36 strain gages and one linear variable displacement transducer. A digital photogrammetric system was used to obtain full field displacements and strains on the smooth (unstiffened) side of the panel. The experimental data were compared with the strains and out-of-plane deflections from a high-fidelity nonlinear finite element analysis.

Mulani, Sameer B.↗
NASA NTRS2014

Ground Operations Autonomous Control and Integrated Health Management

An intelligent autonomous control capability has been developed and is currently being validated in ground cryogenic fluid management operations. The capability embodies a physical architecture consistent with typical launch infrastructure and control systems, augmented by a higher level autonomous control (AC) system enabled to make knowledge-based decisions. The AC system is supported by an integrated system health management (ISHM) capability that detects anomalies, diagnoses causes, determines effects, and could predict future anomalies. AC is implemented using the concept of programmed sequences that could be considered to be building blocks of more generic mission plans. A sequence is a series of steps, and each executes actions once conditions for the step are met (e.g. desired temperatures or fluid state are achieved). For autonomous capability, conditions must consider also health management outcomes, as they will determine whether or not an action is executed, or how an action may be executed, or if an alternative action is executed instead. Aside from health, higher level objectives can also drive how a mission is carried out. The capability was developed using the G2 software environment (www.gensym.com) augmented by a NASA Toolkit that significantly shortens time to deployment. G2 is a commercial product to develop intelligent applications. It is fully object oriented. The core of the capability is a Domain Model of the system where all elements of the system are represented as objects (sensors, instruments, components, pipes, etc.). Reasoning and decision making can be done with all elements in the domain model. The toolkit also enables implementation of failure modes and effects analysis (FMEA), which are represented as root cause trees. FMEA's are programmed graphically, they are reusable, as they address generic FMEA referring to classes of subsystems or objects and their functional relationships. User interfaces for integrated awareness by operators have been created.

Figueroa, Fernando↗
NASA NTRS2013

Automated Generation of Fault Management Artifacts from a Simple System Model

Our understanding of off-nominal behavior - failure modes and fault propagation - in complex systems is often based purely on engineering intuition; specific cases are assessed in an ad hoc fashion as a (fallible) fault management engineer sees fit. This work is an attempt to provide a more rigorous approach to this understanding and assessment by automating the creation of a fault management artifact, the Failure Modes and Effects Analysis (FMEA) through querying a representation of the system in a SysML model. This work builds off the previous development of an off-nominal behavior model for the upcoming Soil Moisture Active-Passive (SMAP) mission at the Jet Propulsion Laboratory. We further developed the previous system model to more fully incorporate the ideas of State Analysis, and it was restructured in an organizational hierarchy that models the system as layers of control systems while also incorporating the concept of "design authority". We present software that was developed to traverse the elements and relationships in this model to automatically construct an FMEA spreadsheet. We further discuss extending this model to automatically generate other typical fault management artifacts, such as Fault Trees, to efficiently portray system behavior, and depend less on the intuition of fault management engineers to ensure complete examination of off-nominal behavior.

Spinup and Orient↗
NASA NTRS2017

A Novel UAV Electric Propulsion Testbed for Diagnostics and Prognostics

This paper presents a novel hardware-in-the-loop (HIL) testbed for systems level diagnostics and prognostics of an electric propulsion system used in UAVs (unmanned aerial vehicle). Referencing the all electric, Edge 540T aircraft used in science and research by NASA Langley Flight Research Center, the HIL testbed includes an identical propulsion system, consisting of motors, speed controllers and batteries. Isolated under a controlled laboratory environment, the propulsion system has been instrumented for advanced diagnostics and prognostics. To produce flight like loading on the system a slave motor is coupled to the motor under test (MUT) and provides variable mechanical resistance, and the capability of introducing nondestructive mechanical wear-like frictional loads on the system. This testbed enables the verification of mathematical models of each component of the propulsion system, the repeatable generation of flight-like loads on the system for fault analysis, test-to-failure scenarios, and the development of advanced system level diagnostics and prognostics methods. The capabilities of the testbed are extended through the integration of a LabVIEW-based client for the Live Virtual Constructive Distributed Environment (LVCDC) Gateway which enables both the publishing of generated data for remotely located observers and prognosers and the synchronization the testbed propulsion system with vehicles in the air. The developed HIL testbed gives researchers easy access to a scientifically relevant portion of the aircraft without the overhead and dangers encountered during actual flight.

Gorospe, George E., Jr.↗
NASA NTRSDate not supplied

Reliability Issues with Polymer and MnO2 Tantalum Capacitors for Space Applications

This work gives a comparative analysis of degradation processes, failure modes and mechanisms in MnO2 and polymer technology capacitors. Analyzed conditions include effects of vacuum and radiation, soldering (pop-corning), long-term storage and operation at high temperatures, stability at low and high temperatures, and anomalous transients. Screening and qualification procedures to assure space-grade quality of CPTCs are suggested.

tantalum capacitors↗
NASA NTRSDate not supplied

Reliability Issues with Polymer and MnO2 Tantalum Capacitors for Space Applications

This presentation gives a comparative analysis of degradation processes, failure modes and mechanisms in MnO2 and polymer technology capacitors. Analyzed conditions include effects of vacuum and radiation, soldering (pop-corning), long-term storage, operation at high temperatures, stability at low and high temperatures, and anomalous transients. Screening and qualification procedures to assure space-grade quality of CPTCs are suggested.

capacitor↗
NASA NTRS2020

Quasi-Static and Dynamic Analysis of Composite Panels: Challenges in Engineering-Level Commercial Software

In engineering applications, where analysis time and efficiency are essential, analytical models and commercially available finite element (FE) material models are the two mainstream methods used to analyze composite crush scenarios. A reliable numerical model addressing the crushing response of composite materials requires a nonlinear progressive damage analysis which includes appropriate failure mechanisms such as matrix cracking, fragmentation, delamination, and fiber breakage. One might be able to address all these interacting failure responses through implementation/validation of a user defined material model or by utilization of a commercially available model, the latter being the most efficient engineering approach. In this paper, the quasi-static and dynamic crushing response of composite specimens, consisting of a C-channel and a corrugated geometry manufactured with carbon fiber/epoxy matrix fabric, are modeled using the progressive composite damage model within ABAQUS. The novel part of this work, which has not been previously addressed in the literature, is the utilization of a detailed parametric study to optimize composite damage model parameters for a given quasi-static crush simulation in ABAQUS. C-channel experiments were used to calibrate the model and then refine/optimize a set of material parameters that best fit the experimental results. These identical parameters were then used to simulate the crush response of the corrugated channel specimens, thereby making it a pure prediction and not a double recalibration. Next, the dynamic response of both panels were predicted, further confirming the predictive capability of the developed numerical model. The effect of parameter variation on the crush response is fully documented for future use in engineering applications utilizing this specific ABAQUS damage model.

Paria Naghipour↗
NASA NTRSDate not supplied

3D Representation of UAV-obstacle Collision Risk Under Off-nominal Conditions

Safe operations of autonomous unmanned aerial vehicles (UAVs) in low-altitude airspace with beyond visual line-of-sight (BVLOS) flights demand robust risk monitoring of airspace as well as of people and property on ground. One of the safety critical factors for UAV flights is the risk of collision with static and dynamic obstacles in proximity to its flight path. This paper presents a detailed formulation of risk of obstacle collision incorporating the effects of off-nominal conditions introduced by component failures, degraded controllability and environmental disturbances such as wind gusts. The risk is represented in terms of a matrix with rows corresponding to the likelihood of occurrence of collision and columns representing severity of collision to the vehicle and surrounding structures. Risk likelihood is generated using a Bayesian Belief Network (BBN) that compiles knowledge from related Failure Modes and Effects Analysis (FMEAs) and Subject Matter Experts (SMEs) to determine the probability of collision based on on-board sensor measurements indicative of vehicle health and controllability. Risk severity is computed utilizing a point-mass 3D kinematic model of the vehicle in presence of wind. The proposed risk factor is demonstrated on real flight data from experimental flights of an octocopter at NASA Langley Research Center in presence of simulated obstacles and wind conditions. Effect of varying wind conditions, level of controllability and obstacle measurement noise on the risk factor is demonstrated. The proposed approach enables risk-informed decision making for timely mitigation of current and future unsafe events in autonomous systems.

risk analysis↗
NASA NTRSDate not supplied

What Went Wrong: A Survey of Wildfire UAS Mishaps through Named Entity Recognition

Increasingly, unmanned aircraft systems (UAS) are being applied to wildfire incidents for tasks such as mapping, aerial ignition, and delivery. As a result, aviation incident reporting systems for wildfires are beginning to accumulate data related to UAS mishaps in wildfire response. In this research, we apply state-of-the-art natural language processing (NLP) techniques to develop a custom Named Entity Recognition (NER) model which extracts entities relevant to safety analysts. The custom NER model is built by fine-tuning an existing Bidirectional Encoder Representations from Transformers (BERT) model, resulting in a generalizable NER model that can extract engineering relevant entities including failure modes, causes, effects, control processes, and recommendations from failure-relevant text. This model performs passably, with a weighted average f1 score of 0.33 across entity types, indicating more labeled training data is needed. Extracted entities are used to form a Failure Modes and Effects Analysis (FMEA)-style survey of wildfire UAS mishaps reported using the SAFECOM system. Similar mishaps are manually clustered and reported as single rows within an FMEA. Foreach cluster, we compute frequency, severity, and overall riskin accordance with FAA standards. This methodology can beapplied as part of a broader safety management system totrack trends in mishaps (e.g., likelihood, severity) and discoverknowledge (e.g., causes, effects) that can be utilized to improvesafety outcomes and system performance.

Machine Learning↗
NASA NTRSDate not supplied

SPIKE-Dx : A Low-Power High-Throughput Fault Diagnostics Tool using Spiking Neural Networks for Constrained Systems

Diagnostic systems are important for many aerospace systems, which are severely limited in available power, like cubesats or UAVs. Therefore, traditional diagnostics systems cannot be used due to their substantial footprint and constraints. In this paper, we present our very low power diagnostic tool SPIKE-DX to monitor critical systems with constrained computational and energy resources. This is made possible through spiking neural networks (SNNs), which are executable within optimized simulation environments and further implemented on on cutting-edge neuromorphic hardware. Based upon FMEA (Failure Mode and Effect Analysis) framework, Diagnostic Bayesian Networks (DBNs) can be constructed that provide powerful means for diagnostic reasoning. In this paper, we describe such DBNs and a method to automatically translate the DBN into highly structured networks of spiking neurons for execution in SPIKE-DX.

Spiking Neural Networks↗
DOE OSTI2023

Probabilistic Risk Assessment of a Light Water Reactor Coupled with a High-Temperature Electrolysis Hydrogen Production Plant

This paper presents recent updates on the Level 1 Probabilistic Risk Assessment (PRA) of Light Water Reactors (LWRs) coupled with a hydrogen production plant. It provides the overview of past results on the PRA for Pressurized Water Reactors (PWRs) and Boiling Water Reactors (BWRs) coupled to a 1150 MW High Temperature Electrolysis Facility (HTEF), as well as the latest research results for a smaller 100 MW HTEF facility. Differences between the two HTEF designs are listed. Key differences include the amount and quality of diverted LWR steam, complexity of the Heat Extraction System (HES), and the electrical power source for the HTEF plant. A Failure Mode and Effect Analysis (FMEA) was conducted for the new HTEF design, and the LWR PRA models were modified in the SAPHIRE risk assessment tool to account for the newly identified risk contributors. These include the steam loss event at the HES system, the electrical overcurrent event at the HTEF facility and at the transmission line from the LWR plant, and the hydrogen detonation event at the HTEF facility. The coupling of LWRs with a 100 MW HTEF increases the frequency of several initiating events. For the reference PWR, the largest frequency increase is for the steam line break event at 5.5%. While for the reference BWR, the largest frequency increase is for the switchyard-related Loss of Offsite Power (LOOP) event at 0.11%. The overall plant risk increases by 6.56% and 0.03% for PWR and BWR reference plants respectively. It is found that these risk metrics satisfy the safety criteria of both 10 CFR 50.59 and Regulatory Guide 1.174 licensing pathways.

08 HYDROGEN↗
DOE OSTI2021

Dynamic Probabilistic Safety Assessment Studies for Advanced Reactor Using RAVEN

Probabilistic Safety Assessment (PSA) is used extensively to evaluate the risks associated with complex engineering systems like Nuclear Power Plants (NPPs). Current PSA models are based on the Event-Tree/Fault-Tree (ET/FT) methodology. ET and FT models are static and are based on Boolean logic approaches. In the past, concerns have been raised in the literature regarding the capability of the traditional static modelling approaches to adequately account for the impact of process, hardware, software, firmware and human interactions on the stochastic system behaviour. To overcome the limitations of the traditional approach to PSA, several dynamic PSA methodologies have been proposed. One of the dynamic PSA methodologies used for dynamic evaluations is Dynamic Event Tree (DET) framework which can be used to assess the impact of the parameter variability and scenario dynamics on the PSA model for the initiating event. The DET framework couples the stochastic model (number of component/trains that start on demand, operator action timing, etc.) with a Thermal-Hydraulic (TH) model of the plant. This paper explores the use of DET along with a case study on advanced reactor. The initiating event selected for the study was Class IV power supply failure event. The TH analysis considering uncertainty in various parameters was performed using RELAP5 and Reactor Analysis and Virtual control ENvironment (RAVEN) tool. Based on the uncertainty analysis, it is concluded that the peak clad temperatures (PCT) are within the limits in all the code runs implying a high-degree of safety margin. However, variation in time to reach the PCT was observed among the code runs and the mean time to reach the PCT was found to be around 8590sec (approximately 2.4 hours). Hence, sufficient time margin is available for human intervention and the operator might have a relatively stress-free state during such an accident scenario. Due to the static nature of the traditional PSA models, the safety margin available was lesser, whereas, with the help of dynamic PSA models, one can demonstrate that the actual available safety margin is more in the present case study and is valuable input from the design point of view.

99 GENERAL AND MISCELLANEOUS↗