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At least 487 records · Page 27

Lewis inverse design code (LINDES): Users manual

The method of complex characteristics and hodograph transformation for the design of shockless airfoils was introduced by Bauer, Garabedian, and Korn and has been extended by the author to design subcritical and supercritical cascades with high solidities and large inlet angles. This new capability was achieved by introducing a new conformal mapping of the hodograph domain onto an ellipse and expanding the solution in terms of Chebyshev polynomials. A new computer code, the NASA Lewis inverse design code, was developed based on this idea. This new design code is an efficient method for the design of airfoils in cascade. In particular, the design of subcritical cascades of airfoils is a very fast, robust, and versatile process. The inverse design code can be made to interact with a turbulent boundary layer calculation to obtain airfoils with no separated flows at the design condition. This report is intended to serve as a users manual for this design code. Material previously reported by the author is included here for completeness and quick access to the user. The manual contains a description of the method followed by a discussion of the design procedure and examples. The input parameters necessary to run the code are then described and their default values given. Output listings corresponding to six different blade shapes designed with the code are given, as well as the necessary input data to reproduce the computer runs. The examples have been chosen to show that a wide range of applications can be covered with the code, ranging from supercritical propeller sections to wind tunnel turning vanes that can operate with a large inlet flow angle range.

Sanz, Jose M.↗

SPH Modeling of Biomass Granular Flow: Engineering Application in Hoppers and Augers

Numerical modeling of granular biomass material flow in handling operations is indispensable to decipher flow upsets, commonly manifested as clogging and jamming in hoppers and augers. With a computational tool developed based on smoothed particle hydrodynamics (SPH), we simulated the hopper flow and auger feeding of six granular biomass materials. The good agreement between the experimental and numerical flow rates demonstrated the capability of the developed SPH solver in modeling the complicated flow of granular biomass materials. Further, the impact of physical and numerical parameters is investigated, and the major results show that the hopper flow pattern is controlled by shear band evolution; hopper clogging is collectively influenced by the opening size, wall friction, and material packing, and the impact of material compressibility on the auger feed rate is minimal. These parametric studies validate the solver’s robustness in simulating biomass flow in handling equipment and demonstrate that the SPH computational tool can provide insights about granular flow mechanics to facilitate handling equipment design and optimize handling operations.

09 BIOMASS FUELS↗

Thermal Reservoir Networks for Modularly Expandable Thermal Microgrids

The Department of Defense (DoD) faces the substantial challenge of cost-effectively retrofitting one to two installations per month, each comprising approximately 1,000 buildings, to improve resilience, reduce energy consumption, and enhance energy supply security. Achieving these objectives requires optimal system selection and effective risk mitigation during system integration. To address this need, we introduce Platform-Based Design (PBD), a structured, hierarchical methodology adapted from other industrial sectors to the domain of energy system retrofits. We demonstrate the effectiveness of PBD through a techno-economic feasibility study comparing geothermal-coupled thermal energy networks (TENs) with conventional energy systems for heating, cooling, and powering 17 buildings at Joint Base Andrews (JBA) in Maryland. Our analysis illustrates that the PBD approach enables rigorous, data-driven, sequential decision making, resulting in a family of Pareto-optimal systems, among which the TEN emerged as the most promising solution. The selected TEN design integrates geothermal borefields, heat recovery heat pumps, photovoltaic (PV) arrays, and battery storage. Compared to the baseline system – gas heating combined with air-source chillers – the proposed TEN reduces annual imported energy by 74% and peak electricity demand by 45%, achieves a levelized cost of energy of $\$0.210$/kWh, and substantially enhances resilience. Life-cycle costs increase by approximately 6%, and initial investment costs are about 2.5 times higher than the baseline. However, if central plant infrastructure, district loops, and utility-scale PV and battery systems are privately funded and operated, the initial investment would fall below the baseline system cost. Critical to achieving these significant performance improvements were detailed nonlinear dynamic simulations coupling geothermal heat transfer, energy system operation, and realistic feedback control logic. These simulations identified essential design modifications and control strategy refinements that substantially reduced energy use, peak demand, and compressor shortcycling, thereby improving durability and reliability—issues that would have been significantly more expensive to resolve during operation. Additionally, the verification step highlighted sensitivities to key design parameters that could reduce initial investment by approximately $\$2$ million and reduce annual life-cycle costs more than $\$300,000$. We recommend adopting the PBD methodology for future feasibility studies and TEN pilot projects to gain valuable operational experience. Furthermore, we recommend that DoD invest in transferring and scaling the PBD methodology to other installations. This entails developing standardized computational frameworks and component libraries as well as training industry in conducting PBD. Such investments would enable rapid, robust, reliable, and cost-effective retrofits, supporting DoD’s ambitious energy system modernization goals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Image based tracking approaches to AR/C at the Johnson Space Center

Automated Rendezvous and Capture (AR&C) requires the determination of the six degrees of freedom relating two free bodies. Sensor systems that can provide such information have varying sizes, weights, power requirements, complexities and accuracies. One type of sensor system which can provide several key advantages is an image based tracking system, or better known as a machine vision system. By image based tracking we mean that the sensor is some imaging device such as one or more video cameras, from which the tracking parameters necessary to support the rendezvous and capture operations (range, attitude, etc.) can be derived. Image based tracking offers many advantages such as relative hardware simplicity and reprogrammability. These advantages must be weighed against the disadvantages of these systems, such as limited operational range, poorer accuracy at greater distances and sensitivity to lighting conditions. However, with properly designed algorithms and targets these disadvantages can be minimized for many important applications. Rigorous testing in realistic environments can further increase the robustness and reliability of these systems. This presentation describes the facilities used at JSC to support AR&C image based tracking development and the details of our binocular stereo approach to image based tracking.

Fisher, Timothy E.↗

Establishing and Maintaining the Digital Thread of Additively Manufactured Materials and Applications

Additive Manufacturing (AM) and Integrated Computational Materials Engineering (ICME) are complementary enabling technologies for design and manufacturing of “fit-for-purpose” materials. Both technologies will impact rapid material design, reduction in cost- and time-to-market for new applications, and discovery and implementation of new materials. An ICME approach to design, however, requires experimentally validated material models at multiple length and time scales, an integrated framework that can connect analysis tools with one another to ensure the digital thread of an application is maintained, and the manufacturing (e.g., AM) capability to leverage processing-structure-property-performance (PSPP) relationships to achieve spatially varying material properties where desired. AM enables the implementation of the design of an optimized, spatially varying microstructure through careful selection of the processing parameters used during an additively manufactured build. In order to establish these PSPP relations, a large amount of data is necessary, and that data must be properly captured, analyzed and maintained in an information management system that can establish the required traceability between various aspects of the design process to ensure an application’s digital thread is maintained (from design to end of life). Such an information management system must be able to capture feedstock material pedigree, resulting microstructure from various build parameters, subsequent mechanical properties derived from testing, developed material models, and enable spatial variations in material assignment in an engineering application. Furthermore, the information management system should be easily integrated with traditionally engineered materials in a single, centralized platform to enable an ICME optimization tool to explore both types of manufacturing processes. At NASA GRC, a robust, 21st century materials information management system has been previously developed with a focus towards enabling ICME. In this work, GRC’s ICME schema is extended to accommodate additively manufactured materials, enabling storage of both traditionally and additively manufactured materials in the same construct. The methodology for properly capturing additively manufactured materials across the entire material lifecycle is presented, following the previously established database best practices, as a potential framework for establishing PSPP relationships for additively manufactured materials and applying them to engineering applications.

Data management↗

Novel nonwetting solid-infused surfaces for superior fouling mitigation

Fouling is a ubiquitous issue in several environmental and energy applications. Here we introduce novel nonwetting solid-infused surfaces (SIS) with superior anti-fouling characteristics that are durable than conventional nonwetting surfaces in a dynamic flow environment. A systematic study is presented to elucidate the fouling mitigation performance of SIS in comparison to lubricant-infused surface (LIS) and conventional smooth surface. Copper tubes with SIS, LIS or smooth inner walls are fabricated and subjected to accelerated calcium sulfate fouling in a flow fouling experimental setup. Fouling on the various surface types is quantified in terms of asymptotic fouling resistance, and the fundamental morphological differences in the interactions of the foulant and the various surface types are analyzed. Based on a systematic sweep of the parameter combinations using design of experiments and Taguchi analysis, an analytical dependence of asymptotic fouling resistance on the governing parameters namely, Reynolds number, foulant concentration and temperature is derived. The analytical model is shown to predict the asymptotic fouling resistance to within 20% accuracy with a 95% confidence. In addition, for the first time, the effects of shear durability on the fouling mitigation performance of LIS vis-à-vis SIS are studied. It is shown that the novel nonwetting SIS offers a robust option for superior fouling mitigation over LIS in the long run.

42 ENGINEERING↗

Enabling cooperative adaptive cruise control on strings of vehicles with heterogeneous dynamics and powertrains

Recent studies have shown that positive impact of Cooperative Adaptive Cruise Control (CACC) can only be guaranteed as market penetration rate increases. Removing the string homogeneity constraint is essential to encourage widespread adoption. In this work, a hierarchical architecture is proposed to enable CACC on vehicles with not only mixed dynamics but also different powertrain types. A low-level layer deals with the vehicle and powertrain dynamics to provide accurate and consistent reference speed tracking response. The high-level layer uses: (1) a Linear Parameter Varying feedback system to provide loop stability, robustness and enforce a variable time gap policy and (2) a feedforward system that processes Vehicle-to-Vehicle information to enhance string stability and response bandwidth, by dealing with the string heterogeneity. A gap management strategy is built on top of the CACC architecture to handle gap setting changes or cut-in/out situations, via a dynamics constrained time gap trajectory planning algorithm. We report the proposed work has been designed, developed and validated on three different real passenger vehicles on public highways and test tracks, showing the potential of the proposed algorithm to enable robust string stable CACC, despite the different dynamics and powertrains considered.

33 ADVANCED PROPULSION SYSTEMS↗

Design and evaluation of a failure detection and isolation algorithm for restructurable control systems

The use of a decentralized approach to failure detection and isolation for use in restructurable control systems is examined. This work has produced: (1) A method for evaluating fundamental limits to FDI performance; (2) Application using flight recorded data; (3) A working control element FDI system with maximal sensitivity to critical control element failures; (4) Extensive testing on realistic simulations; and (5) A detailed design methodology involving parameter optimization (with respect to model uncertainties) and sensitivity analyses. This project has concentrated on detection and isolation of generic control element failures since these failures frequently lead to emergency conditions and since knowledge of remaining control authority is essential for control system redesign. The failures are generic in the sense that no temporal failure signature information was assumed. Thus, various forms of functional failures are treated in a unified fashion. Such a treatment results in a robust FDI system (i.e., one that covers all failure modes) but sacrifices some performance when detailed failure signature information is known, useful, and employed properly. It was assumed throughout that all sensors are validated (i.e., contain only in-spec errors) and that only the first failure of a single control element needs to be detected and isolated. The FDI system which has been developed will handle a class of multiple failures.

Weiss, Jerold L.↗

Stability robustness improvement of direct eigenspace assignment based feedback systems using singular value sensitivities

A methodology to improve the stability robustness of feedback control systems designed using direct eigenspace assignment techniques is presented. The method consists of considering the sensitivity of the minimum singular value of the return difference transfer matrix at the plant input to small changes in the desired closed-loop eigenvalues and the specified elements of the desired closed-loop eigenvectors. Closed-form expressions for the gradient of the minimum return difference singular value with respect to desired closed-loop eigenvalue and eigenvector parameters are derived. Closed-form expressions for the gradients of the control feedback gains with respect to the specified eigenspace parameters are obtained as an intermediate step. The use of the gradient information to improve the guaranteed gain and phase margins in eigenspace assignment based designs is demonstrated by application to an advanced fighter aircraft.

Garg, Sanjay↗

Stability robustness improvement of direct eigenspace assignment based feedback systems using singular value sensitivities

A methodology to improve the stability robustness of feedback control systems designed using direct eigenspace assignment techniques is presented. The method consists of considering the sensitivity of the minimum singular value of the return difference transfer matrix at the plant input to small changes in the desired closed-loop eigenvalues and the specified elements of the desired closed-loop eigenvectors. Closed-form expressions for the gradient of the minimum return difference singular value with respect to desired closed-loop eigenvalue and eigenvector parameters are derived. Closed-form expressions for the gradients of the control feedback gains with respect to the specified eigenspace parameters are obtained as an intermediate step. The use of the gradient information to improve the guaranteed gain and phase margins in eigenspace assignment based designs is demonstrated by application to an advanced fighter aircraft.

Garg, Sanjay↗

Bias Momentum Sizing for Hovering Dual-Spin Platforms

An atmospheric flight vehicle in hover is typically controlled by varying its thrust vector. Achieving both levitation and attitude control with the propulsion system places considerable demands on it for agility and precision, particularly if the vehicle is statically unstable, or nearly so. These demands can be relaxed by introducing an appropriately sized angular momentum bias aligned with the vehicle's yaw axis, thus providing an additional margin of attitude stability about the roll and pitch axes. This paper describes a methodical approach for trading off angular momentum bias level needed with desired levels of vehicle response due to the design disturbance environment given a vehicle's physical parameters. It also describes several simplifications that provide a more physical and intuitive understanding of dual-spin dynamics for hovering atmospheric vehicles. This approach also mitigates the need for control torques and inadvertent actuator saturation difficulties in trying to stabilize a vehicle via control torques produced by unsteady aerodynamics, thrust vectoring, and unsteady throttling. Simulation results, based on a subscale laboratory test flying platform, demonstrate significant improvements in the attitude control robustness of the vehicle with respect to both wind disturbances and off-center of gravity payload changes during flight.

Lim, Kyong B.↗

Space Launch System Base Heating Test: Sub-Scale Rocket Engine/Motor Design, Development & Performance Analysis

ATA-002 Technical Team has successfully designed, developed, tested and assessed the SLS Pathfinder propulsion systems for the Main Base Heating Test Program. Major Outcomes of the Pathfinder Test Program: Reach 90% of full-scale chamber pressure Achieved all engine/motor design parameter requirements Reach steady plume flow behavior in less than 35 msec Steady chamber pressure for 60 to 100 msec during engine/motor operation Similar model engine/motor performance to full-scale SLS system Mitigated nozzle throat and combustor thermal erosion Test data shows good agreement with numerical prediction codes Next phase of the ATA-002 Test Program Design & development of the SLS OML for the Main Base Heating Test Tweak BSRM design to optimize performance Tweak CS-REM design to increase robustness MSFC Aerosciences and CUBRC have the capability to develop sub-scale propulsion systems to meet desired performance requirements for short-duration testing.

Mehta, Manish↗

Tool-Based Case Studies on Strategic Deployment of Untapped Micro-Pumped Hydro Storage in Michigan

With most classical hydropower sites already utilized and the global push for rapid integration of renewable energy sources accelerating, there is a critical need to identify alternative energy storage solutions. Pumped hydro energy storage, which accounts for the vast majority of global grid-scale storage, remains one of the most cost-effective and long-duration storage technologies available. Hence, this study presents a novel tool designed to assess the untapped potential of inland lakes and reservoirs for micro-PSH, using Michigan’s relatively flat landscape as a case study due to its extensive but underutilized water infrastructure. To ensure accuracy and reliability, the tool incorporates extensive data gathered from authorized sources, covering more than 420 water facilities and potential reservoirs in the state. The tool evaluates key parameters such as horizontal and vertical distances, volume, and the total storage capacity of each reservoir. Its robust assessment framework integrates these metrics to evaluate each site’s potential. The tool’s intuitive interface and geospatial visualizations support actionable insights for planners and scalable deployment of distributed storage infrastructure.

13 HYDRO ENERGY↗

Simulation-driven design optimization of reaction injection molding (RIM) process for polydicyclopentadiene (pDCPD): Minimizing cycle time, defects, and warpage

Replacing metal components in trucks, trailers, and buses with lightweight polymer composites is challenging due to high temperatures and complex manufacturing. The Reaction Injection Molding (RIM) process using Dicyclopentadiene (DCPD) resin offers a solution by producing robust parts with excellent stiffness, impact strength, and resistance properties. Simulations are essential for optimizing this process, predicting defects, and improving quality. However, most commercial software is tailored for thermoplastics, requiring thermoset users to generate their own datasets. In this study, a material data card for DCPD was developed to perform RIM simulations. Design of Experiments (DOE) was used to identify key factors affecting filling, curing, and warpage, aiming to minimize cycle time and defects. The simulations explored varying injection gate parameters (size, location, number) and process conditions (mold/resin temperature, injection/curing pressure). Results showed that gate design significantly impacts filling behavior and defects. A single central gate provided balanced flow with fewer defects, while two corner gates led to more defects. Additionally, lower injection pressure increased filling time, while higher mold temperature accelerated curing but led to more warpage. In conclusion, this optimization framework aims to enhance DCPD part performance and promote sustainable manufacturing by reducing waste and energy consumption.

42 ENGINEERING↗

Varied farm-level carbon intensities of corn feedstock help reduce corn ethanol greenhouse gas emissions

Abstract A reduction in the overall carbon intensity (CI) of a crop-based biofuel can be achieved by cutting down the CI of the biofuel’s feedstock, which in turn correlates significantly to agricultural management practices. Proposals are being made to incentivize low-carbon biofuel feedstocks under U.S. fuel regulatory programs to promote sustainable farming practices by individual farms. For such an incentive scheme to function properly, robust data collection and verification are needed at the farm level. This study presents our collaboration with U.S. private sector companies to collect and verify the corn production data necessary for feedstock-specific CI calculation at the farm level, through a carefully designed questionnaire, to demonstrate the practicality and feasibility of data collection at scale. We surveyed 71 farms that produced 0.2 million metric tons of corn grain in 2018 in a Midwestern U.S. state to obtain information on key parameters affecting corn ethanol feedstock CI, such as grain yields, fertilizer/chemical application rates, and agronomic practices. Feedstock-specific CI was calculated in the unit of grams (g) CO 2 equivalent (CO 2 e) of greenhouse gases per kilogram (kg) of corn produced. Results showed large CI variations—from 119 to 407 g CO 2 e kg −1 of corn—due to the farm-level inventory, while the production-weighted average CI for all surveyed farms was 210 g CO 2 e kg −1 , comparable to the national average CI of 204 g CO 2 e kg −1 . The nitrogen fertilizer type applied and rate were identified as key factors contributing most to CI variations at the farm level. The estimated N 2 O emissions from fertilizer and biomass nitrogen inputs to soil accounted for 51% of the overall farm-level CI and therefore need to be better monitored at farm level with high resolution. We concluded that this feedstock-specific, farm-level CI evaluation has the potential to be used to incentivize low-carbon feedstock for biofuel production.

54 ENVIRONMENTAL SCIENCES↗

Enabling Next Generation Reaction Injection Molding (RIM) for Lightweight Structures

Replacing metal components in trucks, trailers, and buses with lightweight polymer composites is challenging due to high temperatures and complex manufacturing. The Reaction Injection Molding (RIM) process using Dicyclopentadiene (DCPD) resin offers a solution by producing robust parts with excellent stiffness, impact strength, and resistance properties. Simulations are essential for optimizing this process, predicting defects, and improving quality. However, most commercial software is tailored for thermoplastics, requiring thermoset users to generate their own datasets. In this project, a material data card for DCPD was developed to perform RIM simulations. Design of Experiments (DOE) was used to identify key factors affecting filling, curing, and warpage, aiming to minimize cycle time and defects. The simulations explored varying injection gate parameters (size, location, number) and process conditions (mold/resin temperature, injection/curing pressure). Results showed that gate design significantly impacts filling behavior and defects. A single central gate provided balanced flow with fewer defects, while two corner gates led to more defects. Additionally, lower injection pressure increased filling time, while higher mold temperature accelerated curing but led to more warpage. This optimization framework aims to enhance DCPD part performance and promote sustainable manufacturing by reducing waste and energy consumption. This research has been performed in collaborations with McClarin Composites. The research outcome has been submitted to the Journal of Manufacturing Processes.

36 MATERIALS SCIENCE↗

Structural Reliability Using Probability Density Estimation Methods Within NESSUS

A reliability analysis studies a mathematical model of a physical system taking into account uncertainties of design variables and common results are estimations of a response density, which also implies estimations of its parameters. Some common density parameters include the mean value, the standard deviation, and specific percentile(s) of the response, which are measures of central tendency, variation, and probability regions, respectively. Reliability analyses are important since the results can lead to different designs by calculating the probability of observing safe responses in each of the proposed designs. All of this is done at the expense of added computational time as compared to a single deterministic analysis which will result in one value of the response out of many that make up the density of the response. Sampling methods, such as monte carlo (MC) and latin hypercube sampling (LHS), can be used to perform reliability analyses and can compute nonlinear response density parameters even if the response is dependent on many random variables. Hence, both methods are very robust; however, they are computationally expensive to use in the estimation of the response density parameters. Both methods are 2 of 13 stochastic methods that are contained within the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) program. NESSUS is a probabilistic finite element analysis (FEA) program that was developed through funding from NASA Glenn Research Center (GRC). It has the additional capability of being linked to other analysis programs; therefore, probabilistic fluid dynamics, fracture mechanics, and heat transfer are only a few of what is possible with this software. The LHS method is the newest addition to the stochastic methods within NESSUS. Part of this work was to enhance NESSUS with the LHS method. The new LHS module is complete, has been successfully integrated with NESSUS, and been used to study four different test cases that have been proposed by the Society of Automotive Engineers (SAE). The test cases compare different probabilistic methods within NESSUS because it is important that a user can have confidence that estimates of stochastic parameters of a response will be within an acceptable error limit. For each response, the mean, standard deviation, and 0.99 percentile, are repeatedly estimated which allows confidence statements to be made for each parameter estimated, and for each method. Thus, the ability of several stochastic methods to efficiently and accurately estimate density parameters is compared using four valid test cases. While all of the reliability methods used performed quite well, for the new LHS module within NESSUS it was found that it had a lower estimation error than MC when they were used to estimate the mean, standard deviation, and 0.99 percentile of the four different stochastic responses. Also, LHS required a smaller amount of calculations to obtain low error answers with a high amount of confidence than MC. It can therefore be stated that NESSUS is an important reliability tool that has a variety of sound probabilistic methods a user can employ and the newest LHS module is a valuable new enhancement of the program.

Chamis, Chrisos C.↗

Alternate Communications Spectrum Study (ACSS) for Aviation Data Links (ADL)

The aim of the work was to identify the key factors involved in the use of alternate spectrum in various bands for a future integrated CNS data link. The study focused on systems and spectral bands that can deliver VDL-or-higher data rates in a two-way communication setting (including air-ground, ground-air, and air-air modes of operation), with multiple platforms (aircraft) operating in the same local environment. We begin with a review of the initial task list, and the final task list. The final task list contained a focus upon spectral availability and related systems that could be affected by the deployment of a new aviation data link (ADL) system. Most of this addresses the lower few layers of the communications protocol stack. A brief review of current related efforts in the aeronautical community is then provided, in which we describe several systems and programs of interest. Participation in some of these efforts is recommended. We also delineate several of the advantages and disadvantages of these system/efforts, in view of anticipated requirements of a new ADL. Desired attributes of a new ADL system are then discussed, and a connection with existing systems is made. The need to consider a wider set of alternative systems and technologies is described, and the beneficial aspects of a particular transmission technique- spread spectrum-are discussed. We then discuss in more detail several potential spectral regions, in terms of propagation conditions, available technology, spectrum availability, and waveform selection. Some comments on the need for standardization are also provided. We note that none of the existing systems described will likely meet the full range of desired features of a new ADL, but that several systems and spectral regions offer promise in terms of one or more characteristics. A system design and analysis approach is then provided. In this, we again focus on the lower few layers of the protocol stack, and aim to capture the main features and parameters that must be selected in the design. Two appendices show example versions and initial results of the first few technical steps in the design approach. Some conclusions are then drawn, and in the final section, recommendations are provided, the most important of which are repeated here: 1. Continue the effort begun here. As detailed in this report, we have only uncovered much of the work that needs to be done in order to provide the foundation for a flexible, high- performance, robust ADL. 2. Seize the opportunity to begin testing in the MLS band. The wide bandwidths and low level of usage of this band make it an ideal one for proof-of-concept type testing. Other (non- aeronautical) organizations are likely to make claims on the band if it is not being used. The primary conclusion is that there is a real and pressing need for a new aviation data link. vi

Matolak, David W.↗