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At least 1,225 records · Page 68

Thermal Cycling for Development of Hybrid Fuel for a Notional Mars Ascent Vehicle

A Mars Ascent Vehicle (MAV) would be a critical part of a potential Mars sample return campaign. As currently envisioned, the MAV would launch samples from Mars into Mars orbit. Challenging requirements would be placed on a MAV as it would need to be able to survive in the harsh Martian environment which can get as cold as -120°C in the winter. At these cold temperatures, survival heating could be necessary to keep the MAV within the allowable flight temperature range. Estimates for survival heating power show that a fuel capable of operating at low temperature would significantly reduce the total required energy of the MAV. This has led to consideration of a hybrid propulsion system due to its anticipated low temperature capability. A new wax-based fuel, SP7, has been developed for a notional MAV mission. Thermal modeling of the fuel in the Mars environment was completed in order to estimate the temperature response of the fuel during Mars diurnal temperature cycling. Preliminary thermal testing was conducted to determine the max temperature range, radial gradient, and ramp rate the fuel could tolerate without cracking. The modeling and preliminary testing was used to develop a comprehensive, 100-day thermal cycling campaign. A total of 200 cycles are planned that are representative of 200 Martian diurnal cycles, roughly one-third of a Martian year. After 150 cycles, the fuel samples show no signs of cracking that would jeopardize the rocket’s performance. Though not yet complete, this testing is showing that SP7 has the potential to successfully be used on a MAV mission.

Farias, Edgardo↗

Nonlinear vibrations of thin-walled composite frames

A reduced basis technique and a computational procedure are presented for generating the nonlinear vibrational response, and evaluating the first-order sensitivity coefficients of thin-walled composite frames. The sensitivity coefficients are the derivatives of the nonlinear frequency with respect to the material and lamination parameters of the frame. A mixed formulation is used with the fundamental unknowns consisting of both the generalized displacements and stress resultants in the frame. The flanges and webs of the frames are modeled by using geometrically nonlinear two-dimensional shell and plate finite elements. The computational procedure can be conveniently divided into three distinct steps. The first step involves the generation of various-order perturbation vectors, and their derivatives with respect to the material and lamination parameters of the frame, using the Linstedt-Poincare perturbation technique. The second step consists of using the perturbation vectors as basis vectors, computing the amplitudes of these vectors and the nonlinear frequency of vibration, via a direct variational procedure. The third step consists of using the perturbation vectors, and their derivatives, as basis vectors and computing the sensitivity coefficients of the nonlinear frequency via a second application of the direct variational procedure. Numerical results are presented for semicircular thin-walled frames with I and J section, showing the convergence of the nonlinear frequency and the sensitivity coefficients obtained by both the reduced-basis and perturbation techniques.

Noor, Ahmed K.↗

Longitudinal Proximity Effect, Lateral Inverse Proximity Effect, and Nonequilibrium Superconductivity in Transition-Edge Sensors

We have recently shown that normal-metal/superconductor (N /S) bilayer TESs (superconducting Transition-Edge Sensors) exhibit weak-link behavior. Our measurements were explained in terms of a longitudinal proximity effect model in which superconducting order from the higher transition temperature leads is induced into the TES bilayer plane over remarkably long distances (up to 290 micron). Here we extend our understanding to include TESs with added noise-mitigating normal-metal structures (N structures). We explain our results in terms of an effect converse to the longitudinal proximity effect (LoPE), the lateral inverse proximity effect (LaiPE), for which the order parameter in the N /S bilayer is reduced due to the neighboring N structures. We present resistance and critical current measurements as a function of temperature and magnetic field taken on square Mo/Au bilayer TESs with lengths ranging from 8 to 130 micron with and without added N structures. We observe the inverse proximity effect on the bilayer over in-plane distances many tens of microns and find the transition shifts to lower temperatures scale approximately as the inverse square of the in-plane N-structure separation distance, without appreciable broadening of the transition width. We find TESs with added Au structures exhibit weak-link behavior as evidenced by exponential temperature dependence of the critical current and Josephson-like oscillations of the critical current with applied magnetic field. We also present evidence for nonequilbrium superconductivity and estimate a quasiparticle lifetime of 1.8 x 10(exp -10) s for the bilayer. The LoPE model is also used to explain the increased conductivity at temperatures above the bilayer's steep resistive transition.

Sadleir, John E.↗

Effect of gravity on methane-air combustion

Analytical and numerical techniques dealing with the theoretical description of the influence of zero and reduced gravitational acceleration on diffusion flames, with a view to improving understanding of fires in space vehicles, were developed in support of experimental work performed in this area. This was done in order to confirm qualitative understanding of the process, to determine the quantitative accuracy of numerical predictions, and to establish a mathematical model of the process for subsequent use as a predictive and exploratory tool. The following results were accomplished: (1) derivation of differential equations and boundary conditions describing the system, (2) details of the computations, using a FORTRAN computer program, for calculating the flow and heat and mass transfer in two dimensions (both steady and unsteady). It was shown that the experimental behavior can be reproduced with fair accuracy, provided that the time step is sufficiently short.

Elghobashi, S.↗

Frequency domain approach for evaluation of stochastic control of elastic spacecraft

An attempt is made to develop a reduced-order filter for an elastic spacecraft. The frequency-domain approach is resorted to both for arriving at an appropriate ROF and for evaluating the resulting stochastic flight controller. The frequency-domain approach employed is contrasted to the time-domain approach previously utilized by the authors. A linearized deterministic dynamical model of a solar electric propulsion spacecraft is analyzed. Flexibility modes were incorporated profitably into the ROF model, and the stochastic controllers exhibit notching of structural resonances reminiscent of classical notch filters. Accurate estimates of modal parameters (damping, natural frequency) are deemed crucial, and use of worst-case values in the ROF design is recommended.

Larson, V.↗

Nonlinear feedback guidance law for aero-assisted orbit transfer maneuvers

Aero-assisted orbit transfer vehicles have the potential for significantly reducing the fuel requirements in certain classes of orbit transfer operations. Development of a nonlinear feedback guidance law for performing aero-assisted maneuvers that accomplish simultaneous change of all the orbital elements with least vehicle acceleration magnitude is discussed. The analysis is based on a sixth order nonlinear point-mass vehicle model with lift, bank angle, thrust and drag modulation as the control variables. The guidance law uses detailed vehicle aerodynamic and the atmosphere models in the feedback loop. Higher-order gravitational harmonics, planetary atmosphere rotation and ambient winds are included in the formulation. Due to modest computational requirements, the guidance law is implementable on-board an orbit transfer vehicle. The guidance performance is illustrated for three sets of boundary conditions.

Menon, P. K. A.↗

Development of a Probabilistic Dynamic Synthesis Method for the Analysis of Nondeterministic Structures

Accounting for the statistical geometric and material variability of structures in analysis has been a topic of considerable research for the last 30 years. The determination of quantifiable measures of statistical probability of a desired response variable, such as natural frequency, maximum displacement, or stress, to replace experience-based "safety factors" has been a primary goal of these studies. There are, however, several problems associated with their satisfactory application to realistic structures, such as bladed disks in turbomachinery. These include the accurate definition of the input random variables (rv's), the large size of the finite element models frequently used to simulate these structures, which makes even a single deterministic analysis expensive, and accurate generation of the cumulative distribution function (CDF) necessary to obtain the probability of the desired response variables. The research presented here applies a methodology called probabilistic dynamic synthesis (PDS) to solve these problems. The PDS method uses dynamic characteristics of substructures measured from modal test as the input rv's, rather than "primitive" rv's such as material or geometric uncertainties. These dynamic characteristics, which are the free-free eigenvalues, eigenvectors, and residual flexibility (RF), are readily measured and for many substructures, a reasonable sample set of these measurements can be obtained. The statistics for these rv's accurately account for the entire random character of the substructure. Using the RF method of component mode synthesis, these dynamic characteristics are used to generate reduced-size sample models of the substructures, which are then coupled to form system models. These sample models are used to obtain the CDF of the response variable by either applying Monte Carlo simulation or by generating data points for use in the response surface reliability method, which can perform the probabilistic analysis with an order of magnitude less computational effort. Both free- and forced-response analyses have been performed, and the results indicate that, while there is considerable room for improvement, the method produces usable and more representative solutions for the design of realistic structures with a substantial savings in computer time.

Brown, A. M.↗

Multidisciplinary Optimization of Tilt Rotor Blades Using Comprehensive Composite Modeling Technique

An optimization procedure is developed for addressing the design of composite tilt rotor blades. A comprehensive technique, based on a higher-order laminate theory, is developed for the analysis of the thick composite load-carrying sections, modeled as box beams, in the blade. The theory, which is based on a refined displacement field, is a three-dimensional model which approximates the elasticity solution so that the beam cross-sectional properties are not reduced to one-dimensional beam parameters. Both inplane and out-of-plane warping are included automatically in the formulation. The model can accurately capture the transverse shear stresses through the thickness of each wall while satisfying stress free boundary conditions on the inner and outer surfaces of the beam. The aerodynamic loads on the blade are calculated using the classical blade element momentum theory. Analytical expressions for the lift and drag are obtained based on the blade planform with corrections for the high lift capability of rotor blades. The aerodynamic analysis is coupled with the structural model to formulate the complete coupled equations of motion for aeroelastic analyses. Finally, a multidisciplinary optimization procedure is developed to improve the aerodynamic, structural and aeroelastic performance of the tilt rotor aircraft. The objective functions include the figure of merit in hover and the high speed cruise propulsive efficiency. Structural, aerodynamic and aeroelastic stability criteria are imposed as constraints on the problem. The Kreisselmeier-Steinhauser function is used to formulate the multiobjective function problem. The search direction is determined by the Broyden-Fletcher-Goldfarb-Shanno algorithm. The optimum results are compared with the baseline values and show significant improvements in the overall performance of the tilt rotor blade.

Chattopadhyay, Aditi↗

An Evaluation of the High Level Architecture (HLA) as a Framework for NASA Modeling and Simulation

The High Level Architecture (HLA) is a current US Department of Defense and an industry (IEEE-1516) standard architecture for modeling and simulations. It provides a framework and set of functional rules and common interfaces for integrating separate and disparate simulators into a larger simulation. The goal of the HLA is to reduce software costs by facilitating the reuse of simulation components and by providing a runtime infrastructure to manage the simulations. In order to evaluate the applicability of the HLA as a technology for NASA space mission simulations, a Simulations Group at Goddard Space Flight Center (GSFC) conducted a study of the HLA and developed a simple prototype HLA-compliant space mission simulator. This paper summarizes the prototyping effort and discusses the potential usefulness of the HLA in the design and planning of future NASA space missions with a focus on risk mitigation and cost reduction.

Reid, Michael R.↗

Displacement Damage Effects in Solar Cells: Mining Damage From the Microelectronics and Photonics Test Bed Space Experiment

The objective is to develop an improved space solar cell radiation response analysis capability and to produce a computer modeling tool which implements the analysis. This was accomplished through analysis of solar cell flight data taken on the Microelectronics and Photonics Test Bed experiment. This effort specifically addresses issues related to rapid technological change in the area of solar cells for space applications in order to enhance system performance, decrease risk, and reduce cost for future missions.

Hardage, Donna↗

A Morphing Radiator for High-Turndown Thermal Control of Crewed Space Exploration Vehicles

Spacecraft designed for missions beyond low earth orbit (LEO) face a difficult thermal control challenge, particularly in the case of crewed vehicles where the thermal control system (TCS) must maintain a relatively constant internal environment temperature despite a vastly varying external thermal environment and despite heat rejection needs that are contrary to the potential of the environment. A thermal control system is in other words required to reject a higher heat load to warm environments and a lower heat load to cold environments, necessitating a quite high turndown ratio. A modern thermal control system is capable of a turndown ratio of on the order of 12:1, but for crew safety and environment compatibility these are massive multi-loop fluid systems. This paper discusses the analysis of a unique radiator design which employs the behavior of shape memory alloys (SMA) to vary the turndown of, and thus enable, a single-loop vehicle thermal control system for space exploration vehicles. This design, a morphing radiator, varies its shape in response to facesheet temperature to control view of space and primary surface emissivity. Because temperature dependence is inherent to SMA behavior, the design requires no accommodation for control, instrumentation, nor power supply in order to operate. Thermal and radiation modeling of the morphing radiator predict a turndown ranging from 11.9:1 to 35:1 independent of TCS configuration. Stress and deformation analyses predict the desired morphing behavior of the concept. A system level mass analysis shows that by enabling a single loop architecture this design could reduce the TCS mass by between 139 kg and 225 kg. The concept is demonstrated in proof-of-concept benchtop tests.

Cognata, Thomas J.↗

Stratospheric Intrusion-Influenced Ozone Air Quality Exceedences Investigated in MERRA-2

Ozone near the surface is harmful to human health and is a result of the photochemical reaction with both man-made and natural precursor pollutant sources. Therefore, in order to reduce near surface ozone concentrations, communities must reduce anthropogenic pollution sources. However, the injection of stratospheric ozone into the troposphere, known as a stratospheric intrusion, can also lead to concentrations of ground-level ozone exceeding air quality standards. Stratospheric intrusions are dynamical atmospheric features, however, these intrusions have been misrepresented in models and reanalyses until recently, as the features of a stratospheric intrusion are best identified in horizontal resolutions of approximately 50 km or smaller. NASA's Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) reanalysis is a publicly-available high-resolution dataset (~50 km) with assimilated ozone that characterizes stratospheric ozone on the same spatiotemporal resolution as the meteorology. We show that stratospheric intrusions that impact surface air quality are well represented in the MERRA-2 reanalysis. This is demonstrated through a case study analysis of stratospheric intrusion events which were identified by the United States Environmental Protection Agency (EPA) to impact surface ozone air quality in spring 2012 in Colorado. The stratospheric intrusions are identified in MERRA-2 by the folding of the dynamical tropopause under the jet stream and subsequent isentropic descent of dry, O3-rich stratospheric air towards the surface where ozone air quality exceedences were observed. The MERRA-2 reanalysis can support air quality agencies for more rapid identification of the impact of stratospheric air on ground-level ozone.

Knowland, K. Emma↗

Lessons Learned in the Livingstone 2 on Earth Observing One Flight Experiment

The Livingstone 2 (L2) model-based diagnosis software is a reusable diagnostic tool for monitoring complex systems. In 2004, L2 was integrated with the JPL Autonomous Sciencecraft Experiment (ASE) and deployed on-board Goddard's Earth Observing One (EO-1) remote sensing satellite, to monitor and diagnose the EO-1 space science instruments and imaging sequence. This paper reports on lessons learned from this flight experiment. The goals for this experiment, including validation of minimum success criteria and of a series of diagnostic scenarios, have all been successfully net. Long-term operations in space are on-going, as a test of the maturity of the system, with L2 performance remaining flawless. L2 has demonstrated the ability to track the state of the system during nominal operations, detect simulated abnormalities in operations and isolate failures to their root cause fault. Specific advances demonstrated include diagnosis of ambiguity groups rather than a single fault candidate; hypothesis revision given new sensor evidence about the state of the system; and the capability to check for faults in a dynamic system without having to wait until the system is quiescent. The major benefits of this advanced health management technology are to increase mission duration and reliability through intelligent fault protection, and robust autonomous operations with reduced dependency on supervisory operations from Earth. The work-load for operators will be reduced by telemetry of processed state-of-health information rather than raw data. The long-term vision is that of making diagnosis available to the onboard planner or executive, allowing autonomy software to re-plan in order to work around known component failures. For a system that is expected to evolve substantially over its lifetime, as for the International Space Station, the model-based approach has definite advantages over rule-based expert systems and limit-checking fault protection systems, as these do not scale well. The model-based approach facilitates reuse of the L2 diagnostic software; only the model of the system to be diagnosed and telemetry monitoring software has to be rebuilt for a new system or expanded for a growing system. The hierarchical L2 model supports modularity and expendability, and as such is suitable solution for integrated system health management as envisioned for systems-of-systems.

Hayden, Sandra C.↗

Cost Models for MMC Manufacturing Processes

The quality cost modeling (QCM) tool is intended to be a relatively simple-to-use device for obtaining a first-order assessment of the quality-cost relationship for a given process-material combination. The QCM curve is a plot of cost versus quality (an index indicating microstructural quality), which is unique for a given process-material combination. The QCM curve indicates the tradeoff between cost and performance, thus enabling one to evaluate affordability. Additionally, the effect of changes in process design, raw materials, and process conditions on the cost-quality relationship can be evaluated. Such results might indicate the most efficient means to obtain improved quality at reduced cost by process design refinements, the implementation of sensors and models for closed loop process control, or improvement in the properties of raw materials being fed into the process. QCM also allows alternative processes for producing the same or similar material to be compared in terms of their potential for producing competitively priced, high quality material. Aside from demonstrating the usefulness of the QCM concept, this is one of the main foci of the present research program, namely to compare processes for making continuous fiber reinforced, metal matrix composites (MMC's). Two processes, low pressure plasma spray deposition and tape casting are considered for QCM development. This document consists of a detailed look at the design of the QCM approach, followed by discussion of the application of QCM to each of the selected MMC manufacturing processes along with results, comparison of processes, and finally, a summary of findings and recommendations.

Elzey, Dana M.↗

AgMIP Local, National and Global Assessments of Food System Challenges in A Changing Climate

Food systems connect a diverse network of stakeholders around the world, with complex dynamics governing production, processing, transportation, trade and consumption of food products. Extreme conditions can disrupt multiple components of the food system, with systemic connections providing structure that can both buffer and exacerbate risks. Climate change is shifting current practices in agricultural production and the broader food system, encouraging shifts toward more diverse value chains capable of drawing from multiple food producing regions to reduce the chance that an entire value chain be subject to simultaneous impacts. The IPCC Working Group I report assessed that heat waves, fires, floods and severe storms are becoming more pronounced and widespread with each degree of global warming, increasing food system risk. Food system disruptions can also come from outside the climate system, including from viral outbreaks, geopolitical conflict and socioeconomic changes. This presentation will highlight how the Agricultural Model Intercomparison and Improvement Project (AgMIP) develops modeling approaches that connect climate, biophysical and socioeconomic models in order to capture complex responses of the food system and potential interventions by diverse stakeholders in the public and private sectors. Models are applied on a range of scales that match decision contexts. These include households in specific agricultural production regions (e.g., within a country), national-level policymakers considering policies, sustainability and development priorities for a country’s agricultural sector, and global food market models that balance production and consumption around the world with competition for land, water, energy and sustainability priorities. Models are capable of capturing many important responses, but further development is needed to represent key systemic risks and the possibility for additional interventions beyond the farm gate. Improved food system models will provide important insights into our society’s ability to cope with climate change, as well as our ability to identify agricultural adaptation and mitigation opportunities to reduce overall risk.

Food systems↗

Harnessing Virtual Power Plants Reliably: Enabling tools for increased observability, controllability, operation, and aggregation of distributed energy resources

Harnessing virtual power plants enhances the integration of distributed energy resources into utility grids for a sustainable energy future. Virtual power plants (VPPs) aggregate DERs to enhance resource adequacy and reduce emissions. U.S. utilities are exploring various technologies to manage DERs effectively. FERC Order 2222 allows DERs to participate in both wholesale and retail markets. Enhancing observability and controllability of behind-the-meter (BTM) DERs is essential for reliable grid operations. A hierarchical control architecture can improve coordination among residential energy resources. Field tests showed nearly 20% energy savings and 30% peak power reduction during grid events. Effective management of DERs requires enhanced situational awareness to prevent grid congestion. Integrating DER management systems (DERMS) with existing planning tools can improve operational security. Near-real-time grid models can validate optimal resource set points against resource uncertainty. Traditional uninterruptible power supplies (UPS) can be upgraded to support grid services and become part of VPPs. Upgrading UPS systems can reduce costs by 75% and unlock significant battery capacity. New battery management systems and grid-aware controllers are essential for optimizing UPS performance. Continued research and development are necessary to address challenges in integrating DERs into utility grids. Encouraging customer participation in pilot programs is vital for the evolution of VPPs. Here, the shift towards price-responsive DERs and VPPs is expected to enhance energy distribution efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Microwave-Assisted Plastic Upcycling: Dynamic Data Reconciliation, Parameter Estimation, and Kinetic Modeling

Microwave (MW)-assisted catalytic pyrolysis offers a promising pathway for efficient plastic upcycling. This work develops an integrated modeling framework combining dynamic data reconciliation, a temperature-dependent rate model, and a yield model to represent the time-varying production rate of components in MW-assisted LDPE pyrolysis conducted in a batch reactor. An Arrhenius-type rate model with a temperature-dependent reaction order is developed. A biexponential correlation is proposed for the yield of gaseous products that enables to capture the evolving product formation behavior during conversion. In the yield correlation, one term is used to represent the initial increase in yield, reflecting the rapid formation of intermediate or primary products at the early stages of the reaction when a larger fraction of the reactant remains available. As conversion progresses, the influence of this term gradually diminishes. The other term accounts for the subsequent decrease in the predicted yield, representing secondary reactions such as further cracking or coke formation that reduce the concentration of certain products at higher conversion. The model is found to accurately represent reconciled experimental flow rate profiles from an in-house MW-assisted catalytic batch reactor for major products, including ethylene, ethane, 1-butene, and benzene, across 250−350 °C. Ethylene remains the dominant product but decreases from about 41.95% at 250 °C to 30.14% at 350 °C, while heavier products increase significantly, with 1-butene rising to nearly 8.37% and benzene reaching 2.17% at intermediate temperatures. The model shows that the ethylene production rate can be maximized at around 270 °C. The models developed in this work can be utilized for process optimization, reactor design and scale-up of microwave-assisted plastic conversion technologies, and economic analysis.

Damahe, Harish [West Virginia Univ., Morgantown, W↗

Joint scheduling of energy, fast and primary frequency response reserves in integrated transmission–distribution networks

Inverter-based distributed energy resources (DERs) connected to distribution networks (DNs) can provide fast frequency support, but their reserve deliverability depends on feeder constraints and differs from synchronous primary frequency response (PFR). Existing transmission–distribution coordination studies usually treat reserve generically or neglect feeder-level feasibility, while frequency-security scheduling studies rarely represent distribution feeders explicitly. This paper develops a bi-level day-ahead scheduling framework for integrated transmission–distribution networks that jointly clears energy, transmission-side PFR, and distribution-side fast frequency response (FFR) under exogenous hourly inertia and largest-loss inputs from an external unit commitment (UC) schedule. The transmission problem is modeled with DC-optimal power flow (OPF) and closed-form second-order cone (SOC) frequency-security constraints, whereas each DN is represented by a reserve-aware branch-flow AC-OPF so that scheduled fast reserves remain deliverable during activation. The bi-level problem is reformulated through Karush–Kuhn–Tucker (KKT) conditions into a mixed-integer SOC program, and a penalty term is used to tighten the distribution-network relaxation. In the reduced test system, lower exogenous inertia increased the required primary response from 179.64 MW to 191.08 MW, distribution-side fast response reduced total frequency-response procurement by up to 4.9%, and neglecting distribution constraints overstated the combined distribution-side energy and reserve award by up to 18%. In the expanded study, the largest case was solved in 2.02 s with a 0.00% optimality gap. Time-domain simulations kept the frequency nadir above 59.0 Hz in all tested hours. These results demonstrate the value of fast-response modeling and distribution-feasible reserve delivery in coordinated market clearing.

Noh, Seung-Gil↗