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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 505 records · Page 28

Quantitative assessment of particle dispersion in polymeric composites and its effect on mechanical properties

In this work, an automated image analysis tool is developed to establish quantitative correlations between the particle/cluster size distribution and the mechanical properties of particle reinforced polymer composites (PRPC).This automated image analysis tool is developed within python programming software to process and analyze the microstructural images of the polymerbased composite materials. The spent coffee bean powder (SCBP) reinforced poly-propylene carbonate (PPC) polymer composite with differing wt.% of the filler is selected for the analysis. Detailed statistical analysis of the microstructural images reveals that ‘clustering of clusters’ is also presented in addition to the most commonly reported ‘clustering of particles’, and the distribution of particle/clusters is bimodal. Based on these findings, an effective volume fraction for the filler material is proposed to mainly capture the agglomeration effect. With this effective volume fraction, the standard rule-of-mixture model correctly captures the experimentally measured tensile strength and modulus as a function of filler wt.%. Further, the applicability of this effective volume fraction for other theoretical models is also analyzed. The detailed statistical analysis of the microstructure and the proposed effective volume fraction helps to develop a deeper quantitative understanding of the PRPC than the conventional qualitative correlation of microstructural features with the properties and failure processes.

36 MATERIALS SCIENCE↗

Multidisciplinary concurrent optimization framework for multi-phase building design process

Modern day building design projects require multidisciplinary expertise from architects and engineers across various phases of the design (conceptual, preliminary, and detailed) and construction processes. The Architecture Engineering and Construction (AEC) community has recently shifted gears toward leveraging design optimization techniques to make well-informed decisions in the design of buildings. However, most of the building design optimization efforts are either multidisciplinary optimization confined to just a specific design phase (conceptual/preliminary/detailed) or single disciplinary optimization (structural/thermal/daylighting/energy) spanning across multiple phases. Complexity in changing the optimization setup as the design progresses through subsequent phases, interoperability issues between modeling and physics-based analysis tools used at later stages, and the lack of an appropriate level of design detail to get meaningful results from these sophisticated analysis tools are few challenges that limit multi-phase multidisciplinary design optimization (MDO) in the AEC field. Here this paper proposes a computational building design platform leveraging concurrent engineering techniques such as interactive problem structuring, simulation-based optimization using meta models for energy and daylighting (machine learning based) and tradespace visualization. The proposed multi-phase concurrent MDO framework is demonstrated by using it to design and optimize a sample office building for energy and daylighting objectives across multiple phases. Furthermore, limitations of the proposed framework and future avenues of research are listed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Integration of discrete-event dynamics and machining dynamics for machine tool: Modeling, analysis and algorithms

Machining dynamics research lays a solid foundation for machining operations by providing stable combinations of spindle speed and depth of cut. Furthermore, machine learning has been applied to predict tool life as a function of cutting speed. However, the existing research does not consider the discrete-event dynamics in machine shop, i.e., the machine tool needs to process a series of parts in queue under various practical production requirements. This paper addresses the integration of discrete-event dynamics and machining dynamics to achieve cost savings in machining. A learning-based cost function is first proposed for the studied integrated optimization problem of machine tool. The proposed cost function utilizes the predicted tool life under different stable cutting speeds for further optimizing speed selection of machine tool to deal with the discrete-event dynamics in machine shop. Then, according to the practical production requirements, effective mathematical optimization models are developed for the related integrated optimization problems with the consideration of cost, makespan and due date, respectively. Numerical results show the effectiveness of our proposed methods and also the potential to be used in practice.

Ma, Mason↗

Crash simulation of composite and aluminum helicopter fuselages using a finite-element program

This paper describes a mathematical investigation of the crash-impact responses of an all-composite helicopter cockpit section incorporating an energy absorbing concept and one of conventional aluminum construction, using the Grumman DYCAST finite-element nonlinear structural dynamics computer program. The overall objective of this initial investigation was to explore the application of DYCAST to the design of future helicopter structures. The specific purposes are to assess the value of the finite-element code as a crashworthiness design analysis tool, and to compare the responses of the two fuselage sections. The results indicate that the finite-element simulation is a powerful analysis tool, providing sufficient detail to evaluate individual structural components, and that the crashworthiness of an all-composite cockpit section could be enhanced with energy-absorbing concepts

Winter, R.↗

Operations Modeling for SSF Evolution

The operations required to support the on-orbit Space Station Freedom activities planned or being studied will be complex. Operational capability to perform tasks will be dependent on many factors such as manpower availability, logistics, other tasks being worked and Space Station configuration. This effort uses information available about these and other factors to perform operations analysis for given missions and determine the feasibility of target configuration concepts to support those missions. Studies have been conducted to determine processing requirements for a number of potential evolutionary missions on the Space Station Freedom. These studies have identified the need for growth of the Space Station in various ways. Some of the studies have dealt with the operational needs for the particular mission that they are concerned with, but none have looked at the total evolutionary operations requirement. In order to pursue the subject of overall on-orbit operations to any appreciable level of detail, data bases of operational on-orbit tasks need to be compiled, and an analysis tool is needed to assist the analyst. A number of existing operations tools have been reviewed, and none have been found to satisfactorily perform the functions needed to analyze integrated operations requirements for the evolutionary Space Station Freedom. However, during the tool review, some existing applications were found to provide subsets of the required functionality, and these are being considered for incorporation into the analysis tool.

Ganoe, George G.↗

NASA Spacecraft Trade Modeling System (NSTRDMS)

A rapid mission analysis tool is developed to support the ongoing design of the Lunar Transit trajectory of the Power and Propulsion Element (PPE). A 50-kW class electric propulsion system is envisioned to transit a massive vehicle be-tween a Medium Earth Orbit (MEO) parking orbit and a lunar L2 southern Near Rectilinear Halo Orbit (NRHO). A parameterization is developed by which the Lunar Transit can be analyzed in the context of varying vehicle mass, solar elec-tric propulsion (SEP) configurations, and solar array power output. A rapid and novel mission analysis tool enables a wide array of these trade analyses to be completed without the need for extensive computing resources or time. This tool is shown to be useful in the analysis of a reference trajectory, where changes to the baseline vehicle architecture or off-nominal operational scenarios (such as electric thruster failures) can be rapidly assessed by the mission designer.

Low thrust↗

TRUST Contact Thermal Conductance (TRUST-CTC) Report: FY24

The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainties in Simulations and Tests (TRUST) project is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. Staff development will include cross-discipline collaboration to provide engineers with experience in both numerical simulations and experimental methods. This work uses and provides feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development. TRUST currently includes five testbeds and their associated engineering analysis baseline models (EABMs): 1. contact thermal conductivity, (CTC) 2. nonlinear dynamics, (ND) 3. sensors in environments for accelerometers, (SEA) 4. sensors in environments for fiber optic displacement gages, and (SEFOD) 5. sensors in environments for thermocouples (SETC). The TRUST project uses single-feature testbeds to quantify uncertainties in specific models and experiments and to identify capability development needs that can help to reduce these uncertainties. Each testbed is designed, configured, and tested in collaboration with groups with design and experimental capability: E-14 and MPA-CINT. The complementary simulations are conducted using W-13 analysis tools and stored in model repositories with plans for incremental progress toward EABM requirements. W-13 extends and exercises the testbed simulations in collaboration with experimentalists for uncertainty quantification of current and future materials, geometries, and environments. Additionally, TRUST is intended to provide engineers in W-13 and E-14 with experience in both numerical simulations and experimental methods through cross-discipline collaborations. Following the introduction to the TRUST project, the remainder of this report focuses on experimental and analytical efforts conducted in Fiscal Year (FY) 2024 relevant to the TRUST Contact Thermal Conductance (CTC) testbed.

42 ENGINEERING↗

A Probabilistic Approach to Model Update

Finite element models are often developed for load validation, structural certification, response predictions, and to study alternate design concepts. In rare occasions, models developed with a nominal set of parameters agree with experimental data without the need to update parameter values. Today, model updating is generally heuristic and often performed by a skilled analyst with in-depth understanding of the model assumptions. Parameter uncertainties play a key role in understanding the model update problem and therefore probabilistic analysis tools, developed for reliability and risk analysis, may be used to incorporate uncertainty in the analysis. In this work, probability analysis (PA) tools are used to aid the parameter update task using experimental data and some basic knowledge of potential error sources. Discussed here is the first application of PA tools to update parameters of a finite element model for a composite wing structure. Static deflection data at six locations are used to update five parameters. It is shown that while prediction of individual response values may not be matched identically, the system response is significantly improved with moderate changes in parameter values.

Horta, Lucas G.↗

Reliability and Productivity Modeling for the Optimization of Separated Spacecraft Interferometers

As technological systems grow in capability, they also grow in complexity. Due to this complexity, it is no longer possible for a designer to use engineering judgement to identify the components that have the largest impact on system life cycle metrics, such as reliability, productivity, cost, and cost effectiveness. One way of identifying these key components is to build quantitative models and analysis tools that can be used to aid the designer in making high level architecture decisions. Once these key components have been identified, two main approaches to improving a system using these components exist: add redundancy or improve the reliability of the component. In reality, the most effective approach to almost any system will be some combination of these two approaches, in varying orders of magnitude for each component. Therefore, this research tries to answer the question of how to divide funds, between adding redundancy and improving the reliability of components, to most cost effectively improve the life cycle metrics of a system. While this question is relevant to any complex system, this research focuses on one type of system in particular: Separate Spacecraft Interferometers (SSI). Quantitative models are developed to analyze the key life cycle metrics of different SSI system architectures. Next, tools are developed to compare a given set of architectures in terms of total performance, by coupling different life cycle metrics together into one performance metric. Optimization tools, such as simulated annealing and genetic algorithms, are then used to search the entire design space to find the "optimal" architecture design. Sensitivity analysis tools have been developed to determine how sensitive the results of these analyses are to uncertain user defined parameters. Finally, several possibilities for the future work that could be done in this area of research are presented.

Kenny, Sean↗

Aeropropulsive Assessment of a BLI Tail-Cone Thruster Propulsion System for the NASA Common Research Model and a Transonic Truss-Braced Wing Configuration

This paper presents an investigation into the potential benefits of a boundary layer ingestion(BLI) aft fuselage propulsion system, or tail-cone thruster (TCT), when applied to two transport category aircraft: a conventional tube-and-wing configuration based on the NASA Common Research Model (CRM) and a transonic truss-braced wing (TTBW) configuration. Through the ingestion of low-momentum flow developed over the airframe of an aircraft, the TCT propulsion system technology can reduce overall power consumption and hence fuel burn and emissions. However, an accurate assessment of this potential requires the application of high-fidelity analysis tools that can capture the relevant propulsion-airframe integration effects, at least to first order. Toward this end, the present study employs aeropropulsive analysis tools based on the Reynolds-averaged Navier-Stokes equations to estimate the power savings coefficient, measured relative to equivalent non-BLI configurations of a given airframe. Results indicate shaft power savings of 4.1% and 5.9% can be obtained for the boundary-layer ingesting TCT configuration of the CRM and TTBW, respectively. The present study also examines the coupling between airframe aerodynamics and the inlet flow distortion experienced by the TCT of a given aircraft configuration through airframe component sensitivity studies.

AATT↗

Reduced-Order Blade Mistuning Analysis Techniques Developed for the Robust Design of Engine Rotors

The primary objective of this research program is to develop vibration analysis tools, design tools, and design strategies to significantly improve the safety and robustness of turbine engine rotors. Bladed disks in turbine engines always feature small, random blade-to-blade differences, or mistuning. Mistuning can lead to a dramatic increase in blade forced-response amplitudes and stresses. Ultimately, this results in high-cycle fatigue, which is a major safety and cost concern. In this research program, the necessary steps will be taken to transform a state-of-the-art vibration analysis tool, the Turbo-Reduce forced-response prediction code, into an effective design tool by enhancing and extending the underlying modeling and analysis methods. Furthermore, novel techniques will be developed to assess the safety of a given design. In particular, a procedure will be established for using eigenfrequency curve veerings to identify "danger zones" in the operating conditions--ranges of rotational speeds and engine orders in which there is a great risk that the rotor blades will suffer high stresses. This work also will aid statistical studies of the forced response by reducing the necessary number of simulations. Finally, new strategies for improving the design of rotors will be pursued. Several methods will be investigated, including the use of intentional mistuning patterns to mitigate the harmful effects of random mistuning, and the modification of disk stiffness to avoid reaching critical values of interblade coupling in the desired operating range. Recent research progress is summarized in the following paragraphs. First, significant progress was made in the development of the component mode mistuning (CMM) and static mode compensation (SMC) methods for reduced-order modeling of mistuned bladed disks (see the following figure). The CMM method has been formalized and extended to allow a general treatment of mistuning. In addition, CMM allows individual mode mistuning, which accounts for the realistic effects of local variations in blade properties that lead to different mistuning values for different mode types (e.g., mistuning of the first torsion mode versus the second flexural mode). The accuracy and efficiency of the CMM method and the corresponding Turbo-Reduce code were validated for an example finite element model of a bladed disk.

Min, James B.↗

An Overview of the Thermal Challenges of Designing Microgravity Furnaces

In the last few years, Marshall Space Flight Center has become heavily involved in a wide variety of microgravity projects that require furnaces, with hot zone temperatures ranging from 300 C to 2300 C, requirements for isothermal and gradient processing, and both semi-conductor and metal materials. On these types of projects, the thermal engineer is a key player in the design process. These furnaces present unique challenges to the thermal designer. One challenge is designing a sample containment system that achieves dual containment, yet allows a high radial heat flux. Another challenge is providing a high axial gradient but a very low radial gradient. These furnaces also present unique challenges to the thermal analyst. First, there are several orders of magnitude difference in the size of the thermal "conductors" between various parts of the model. A second challenge is providing high fidelity in the sample model, and connecting the sample with the rest of the furnace model, yet maintaining some sanity in the number of total nodes in the model. The purpose of this paper is to present an overview of the challenges involved in designing and analyzing microgravity furnaces and how some of these challenges have been overcome. The thermal analysis tools presently used to analyze microgravity furnaces and how they have been applied will be explained. Challenges for the future and a description of future analysis tools will be given.

Westra, Douglas G.↗

Nonlinear Thermal Analyses of a Liquid Hydrogen Tank Wall

A thermal evaluation of a composite tank wall design for a liquid hydrogen tank was performed in the present study. The primary focus of the current effort was to perform one-dimensional, temperature nonlinear, transient thermal analyses to determine the through-the-thickness temperature profiles. These profiles were used to identify critical points within the flight envelope that could have detrimental effects on the adhesive bondlines used in the construction of the tank wall. Additionally, this paper presents the finite element models, analysis strategies, and thermal analysis results that were determined for several vehicle flight conditions. The basic tank wall configuration used to perform the thermal analyses consisted of carbon-epoxy facesheets and a Korex honeycomb core sandwich that was insulated with an Airex cryogenic foam and an Alumina Enhanced Thermal Barrier (AETB-12). Nonlinear, transient thermal analyses were conducted using the ABAQUS finite element code. Tank wall models at a windward side location on the fuel tank were analyzed for three basic flight conditions: cold-soak (ground-hold), ascent, and re-entry. Additionally, three ambient temperature boundary conditions were applied to the tank wall for the cold-soak condition, which simulated the launch pad cooldown process. Time-dependent heating rates were used in the analyses of the ascent and reentry segments of the flight history along with temperature dependent material properties. The steady-state through-the-thickness temperature profile from the cold-soak condition was used as the initial condition for the ascent analyses. Results from the nonlinear thermal analyses demonstrated very good correlation with results from similar models evaluated by Northrop- Grumman using a different analysis tool. Wall through-the-thickness temperature gradients as a function of flight time were obtained for future incorporation into a full-scale thermostructural analysis to evaluate the adhesive bondlines. As a result of the thermal analyses conducted, a sufficient level of confidence was demonstrated in the thermal modeling and analysis capabilities of ABAQUS to warrant future use as a thermo-structural analysis tool to evaluate cryogenic tank wall designs.

Smeltzer, Stanley S., III↗

Air Quality Analysis and Tools For Policy

South Asia is home to some of the most significant air quality challenges in the world. More than 99% of the region’s population is exposed to unhealthy fine particulate matter (PM2.5) concentrations, as defined by the World Health Organization. Recent policy initiatives in South Asia show that air quality policy is a priority, given the health impacts of air pollution. At the same time, capacity and data to assess and address air pollution remains limited in many areas. The main objective of this report is to outline a set of publicly-available tools that can be used to inform policies to improve air quality in South Asia. The report primarily focuses on tools such as emission inventories and integrated modeling systems with country-level resolution and illustrates their air quality assessment capabilities through examples and brief technical summaries. The report focuses on: (a) the Community Emissions Data System (CEDS) that provides historical emissions of key pollutants for all countries in South Asia, and (b) profiles an analysis of Indian air pollution and policy scenarios, using several integrated modeling tools. Both of these examples draw on recent research and data that outlines the scale of the challenge as well as the policy options for reducing air pollution in the region. The report concludes with key recommendations for regional stakeholders working towards mitigating air pollution in South Asia.

54 ENVIRONMENTAL SCIENCES↗

TRUST Sensors in Environments: Fiber Optic Displacement (SE-FOD) Report, Release FY24

The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainty in Simulations and Tests (TRUST) project is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to the development, on-target assessment, and qualification of current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. This work uses and provides feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development. Under the TRUST work package, there are five testbeds and their associated engineering analysis baseline models (EABMs): 1. Contact Thermal Conductivity (CTC), 2. Nonlinear Dynamics (ND), 3. Sensors in Environments: Accelerometers (SE-A), 4. Sensors in Environments: Fiber Optic Displacement Gauges (SE-FOD), and 5. Sensors in Environments: Thermocouples (SE-TC). The TRUST project uses single-feature testbeds to quantify uncertainties in specific models and experiments and to identify capability development needs that can help to reduce these uncertainties. Each testbed is designed, configured, and tested in collaboration with groups with design and experimental capability: E-14 and MPA-CINT. The complementary simulations are conducted using W-13 analysis tools and stored in model repositories with plans for incremental progress toward EABM requirements. W-13 extends and exercises the testbed simulations in collaboration with experimentalists for uncertainty quantification of current and future materials, geometries, and environments. Additionally, TRUST is intended to provide engineers in W-13 and E-14 with experience in both numerical simulations and experimental methods through cross-discipline collaborations. Following the introduction to the TRUST project, the remainder of this report focuses on experimental, modeling and simulation, and analysis efforts conducted in FY24 relevant to the TRUST Sensors in Environments: Fiber Optic Displacement (SE-FOD) testbed.

42 ENGINEERING↗

Variance Decomposition of MEDLI2 Reconstructed Heating Using Neural Networks

The Mars Entry, Descent, and Landing Instrumentation (MEDLI2) sensor suite collected data during entry of the Mars 2020 Perseverance rover into Mars’ atmosphere. An inverse estimation of the backshell and heatshield surface aeroheating was performed, using the data from the MEDLI2 Instrumented Sensor Plugs, a network of thermocouples embedded within the thermal protection system across the aeroshell. Monte Carlo analysis was conducted to assess the sensitivity of the surface heat rate, temperature, and heat load to uncertainties in thermocouple depth and material properties. In this paper, a variance decomposition method using Sobol indices was employed to understand the relative contributions of each uncertainty parameter. Performing this analysis using results from the inverse analysis tool FIAT_Opt was found to require incredibly high computation time, and thus machine learning models were trained and evaluated as a surrogate model for FIAT_Opt. This paper demonstrates that machine learning models can be an efficient, accurate alternative to state-of-the-art inverse analysis tools like FIAT_Opt, especially for computationally-expensive processes. Using these models, the sensitivity analysis showed that uncertainties in heat capacity and thermal conductivity were the main drivers for the overall uncertainty in peak reconstructed heating and heat load.

H S Alpert↗

Methods of Increasing Terminal Airspace Flexibility and Control Authority

The focus of the NRA contract is to develop a What-if Analysis Tool for planning Departure Management Programs (DMP) at airports. This final report summarizes the work conducted throughout the base year, with a focus on use case specification for the what-if analysis capability and the implementation of the What-if Analysis Tool and its application to traffic and weather scenarios at Charlotte Douglas International Airport (CLT).

NRA Final Report↗