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NASA NTRS2002

Stability and Control Estimation Flight Test Results for the SR-71 Aircraft With Externally Mounted Experiments

A maximum-likelihood output-error parameter estimation technique is used to obtain stability and control derivatives for the NASA Dryden Flight Research Center SR-71A airplane and for configurations that include experiments externally mounted to the top of the fuselage. This research is being done as part of the envelope clearance for the new experiment configurations. Flight data are obtained at speeds ranging from Mach 0.4 to Mach 3.0, with an extensive amount of test points at approximately Mach 1.0. Pilot-input pitch and yaw-roll doublets are used to obtain the data. This report defines the parameter estimation technique used, presents stability and control derivative results, and compares the derivatives for the three configurations tested. The experimental configurations studied generally show acceptable stability, control, trim, and handling qualities throughout the Mach regimes tested. The reduction of directional stability for the experimental configurations is the most significant aerodynamic effect measured and identified as a design constraint for future experimental configurations. This report also shows the significant effects of aircraft flexibility on the stability and control derivatives.

Moes, Timothy R.↗

NASA NTRSDate not supplied

Design and Hardware Progress on a Magnetically-Geared Actuator for Extremely Cold Lunar Environments

Introduction: Under the Motors for Dusty and Extremely Cold Environments (MDECE) Project, NASA Glenn Research Center is developing a magnetically-geared actuator for extremely cold space environments to avoid the wiring and significant efficiency penalty associated with heating grease-lubricated actuators as well as the stringent life and loading constraints imposed by dry film lubricated mechanical gears. The heating penalty can be equivalent to up to a 90% efficiency reduction in permanently shadowed regions on the Moon. This poster or presentation will summarize the progress made over the past 6-12 months on designing the fully-functional actuator and building a proof-of-concept actuator and testing it in an ambient environment. Design Progress: A critical design review was successfully completed at the end of June 2023. This presentation will touch on the key highlights from that review in the areas of electro-magnetic design and optimization, bearing optimization, thermal analysis, structural analysis, and mechanical design and manufacturing. The predicted technical performance measures of the actuator will be mentioned. The team is currently finishing some actions from the review and finalizing the drawing package in preparation for hardware procurement. Hardware Progress: Despite some significant delays in receiving fabricated parts and magnetic subassemblies, progress was made in manufacturing and assembling a proof-of-concept version of both the actuator’s magnetically-geared motor (Fig. 1) and the actuator’s cycloidal-type output magnetic gear stage (Fig. 2) [3]. The presentation will mention key lessons learned to date from the fabrication, assembly, and testing of the proof of concept.

Lunar surface↗

DOE OSTI2016

Emissions reduction scenarios in the Argentinean Energy Sector

Here in this paper the LEAP, TIAM-ECN, and GCAM models were applied to evaluate the impact of a variety of climate change control policies (including carbon pricing and emission constraints relative to a base year) on primary energy consumption, final energy consumption, electricity sector development, and CO 2 emission savings of the energy sector in Argentina over the 2010-2050 period. The LEAP model results indicate that if Argentina fully implements the most feasible mitigation measures currently under consideration by official bodies and key academic institutions on energy supply and demand, such as the ProBiomass program, a cumulative incremental economic cost of 22.8 billion US$(2005) to 2050 is expected, resulting in a 16% reduction in GHG emissions compared to a business-as-usual scenario. These measures also bring economic co-benefits, such as a reduction of energy imports improving the balance of trade. A Low CO 2 price scenario in LEAP results in the replacement of coal by nuclear and wind energy in electricity expansion. A High CO 2 price leverages additional investments in hydropower. An emission cap scenario (2050 emissions 20% lower than 2010 emissions) is feasible by including such measures as CCS and Bio CCS, but at a significant cost. By way of cross-model comparison with the TIAM-ECN and GCAM global integrated assessment models, significant variation in projected emissions reductions in the carbon price scenarios was observed, which illustrates the inherent uncertainties associated with such long-term projections. These models predict approximately 37% and 94% reductions under the High CO 2 price scenario, respectively. By comparison, the LEAP model, using an approach based on the assessment of a limited set of mitigation options, predicts a 11.3% reduction under the ‘high’ carbon tax. The main reasons for this difference are differences in assumptions about technology cost and availability, CO 2 storage capacity, and the ability to import bioenergy. In terms of technology pathways, the models agree that fossil fuels, in particular natural gas, will remain an important part of the electricity mix in the core baseline scenario. Finally, according to the models there is agreement that the introduction of a carbon price will lead to a decline in absolute and relative shares of aggregate fossil fuel generation. However, predictions vary as to the extent to which coal, nuclear and renewable energy play a role.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Electric Power Grid and Natural Gas Network Operations and Coordination

In this report, we present findings from three studies related to the coordination of natural gas and electricity system operations. We first propose and demonstrate a modeling platform for examining the interdependence of natural gas and electricity networks based on a direct current unit-commitment and economic dispatch model for the power system and a transient hydraulic gas model for the gas system. We use this platform to analyze the value of day-ahead coordination of power and natural gas network operations and to show the importance of considering gas system constraints when analyzing power systems operation with high penetration of gas generators and variable renewable energy sources. In the second study, we utilize our modeling platform to consider the U.S. Federal Energy Regulatory Commission (FERC) Order 809, issued in 2015 to improve day-ahead and intraday coordination of power and gas systems. Finally, in the third study we expand our modeling platform to focus on market-based coordination of electricity and natural gas system operations for a real system, namely a subset of the power and gas networks in the Front Range region of Colorado. We use real system data to evaluate the benefits of coordination operations under different conditions, including different levels of renewable penetration and the use of time-variant, shaped flow nominations. Our results indicate that coordination at various timescales can contribute to a reduction in curtailed gas in high-stress periods (such as those with large ramps in gas offtakes) and a reduction in energy consumption of gas compressor stations. We find that intraday coordination can reduce total power system production costs and natural gas deliverability constraints, yielding cost and reliability benefits. We observe these benefits for the test system as well as in the Colorado case study, where we find that coordination and shaped flows may provide additional value for systems with high penetration of variable renewable energy. Together, these three studies demonstrate a pathway for integrated gas and electricity grid modeling and for studying the benefits of coordinated operations of these increasingly interdependent energy systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1984

Optimum design of rotor blades for vibration reduction in forward flight

Modern structural optimization techniques are applied to vibration reduction of helicopter rotor blades in forward flight. The objective function minimized consists of the oscillatory vertical hub shears or the hub rolling moments at one particular advance ratio. The behavior constraints are the frequency placements of the blade and the requirement that aeroelastic stability margins, in hover, remain unaffected by the optimization process. The aeroelastic stability and response analysis is based on a fully coupled flap-lag-torsional analysis of the blade. Numerical results are presented for some typical soft-in-plane hingeless rotor configurations indicating a 15-40 percent reduction in vibration levels, as well as a blade which is 20 percent lighter than the initial design. These results imply that structural optimization techniques can yield substantial practical benefits in the design process of rotor systems.

Friedmann, P. P.↗

DOE OSTI2024

Mapping the global distribution of C 4 vegetation using observations and optimality theory

Plants with the C 4 photosynthesis pathway typically respond to climate change differently from more common C 3 -type plants, due to their distinct anatomical and biochemical characteristics. These different responses are expected to drive changes in global C 4 and C 3 vegetation distributions. However, current C 4 vegetation distribution models may not predict this response as they do not capture multiple interacting factors and often lack observational constraints. Here, we used global observations of plant photosynthetic pathways, satellite remote sensing, and photosynthetic optimality theory to produce an observation-constrained global map of C 4 vegetation. We find that global C 4 vegetation coverage decreased from 17.7% to 17.1% of the land surface during 2001 to 2019. This was the net result of a reduction in C 4 natural grass cover due to elevated CO 2 favoring C 3 -type photosynthesis, and an increase in C 4 crop cover, mainly from corn (maize) expansion. Using an emergent constraint approach, we estimated that C 4 vegetation contributed 19.5% of global photosynthetic carbon assimilation, a value within the range of previous estimates (18–23%) but higher than the ensemble mean of dynamic global vegetation models (14 ± 13%; mean ± one standard deviation). Our study sheds insight on the critical and underappreciated role of C 4 plants in the contemporary global carbon cycle.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Evaluation of Solid Sorbents as a Retrofit Technology for CO 2 Capture

ADA completed a DOE-sponsored program titled Evaluation of Solid Sorbents as a Retrofit Technology for CO 2 Capture under program DE-FE0004343. During this program, sorbents were analyzed for use in a post-combustion CO 2 capture process. A supported amine sorbent was selected based upon superior performance to adsorb a greater amount of CO 2 than the activated carbon sorbents tested. When the most ideal sorbent at the time was selected, it was characterized and used to create a preliminary techno-economic analysis (TEA). A preliminary 550 MW coal-fired power plant using Illinois #6 bituminous coal was designed with a solid sorbent CO 2 capture system using the selected supported amine sorbent to both facilitate the TEA and to create the necessary framework to scale down the design to a 1 MWe equivalent slipstream pilot facility. The preliminary techno-economic analysis showed promising results and potential for improved performance for CO 2 capture compared to conventional MEA systems. As a result, a 1 MWe equivalent solid sorbent system was designed, constructed, and then installed at a coal-fired power plant in Alabama. The pilot was designed to capture 90% of the CO 2 from the incoming flue gas at 1 MWe net electrical generating equivalent. Testing was not possible at the design conditions due to changes in sorbent handling characteristics at post-regenerator temperatures that were not properly incorporated into the pilot design. Thus, severe pluggage occurred at nominally 60% of the design sorbent circulation rate with heated sorbent, although no handling issues were noted when the system was operated prior to bringing the regenerator to operating temperature. Testing within the constraints of the pilot plant resulted in 90% capture of the incoming CO 2 at a flow rate equivalent of 0.2 to 0.25 MWe net electrical generating equivalent. The reduction in equivalent flow rate at 90% capture was primarily the result of sorbent circulation limitations at operating temperatures combined with pre-loading of the sorbent with CO 2 prior to entering the adsorber. Specifically, CO 2 -rich gas was utilized to convey sorbent from the regenerator to the adsorber. This gas was nominally 45°C below the regenerator temperature during testing. ADA’s post-combustion capture system with modifications to overcome pilot constraints, in conjunction with incorporating a sorbent with CO 2 working capacity of 15 g CO 2 /100 g sorbent and a contact time of 10 to 15 minutes or less with flue gas could provide significant cost and performance benefits when compared to an MEA system.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Demand response event simulator and risk-aware bidding tool for industrial customers

Incentive Based Demand Response (IBDR) program participation delivers financial benefits to the consumers and resiliency benefits to the electricity grid. Effectively participating in these programs as an industrial consumer requires bidding strategies that balance financial risk with operational constraints. Existing bidding tools tend not to fully incorporate stochastic IBDR event modeling, program specific baseline and payment/penalty calculations, or demand reduction process control schemes that account for the cascading impacts of shutdown in complex facilities. Here, this work presents an IBDR event simulator and risk-aware bidding framework tool integrating three key components: a flexible, parameterized demand response event generator that rigorously accounts for program structures and stochasticity, a demand response operational simulation model that generates explicit control strategies for load reduction, and a Monte Carlo simulator to evaluate financial risk for varied capacity bids. A case study at a wastewater treatment plant participating in PG&E's Capacity Bidding Program demonstrates the framework's utility. In the peak capacity price month of August, optimal bidding by the wastewater treatment plant nets a mean IBDR benefit of $101,000 (67% of the August electricity bill) with 0.4% probability of a financial loss. This framework enables industrial operators to make informed bidding decisions, negotiate better program terms with demand response load aggregators, and analyze energy flexibility investments at their facilities. Ultimately, this work reduces participation barriers in IBDR programs and supports the broader goal of enhancing grid reliability and renewable energy integration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

A Novel Emergent Constraint Approach for Refining Regional Climate Model Projections of Peak Flow Timing

Abstract Global climate models (GCMs) are unable to produce detailed runoff conditions at the basin scale. Assumptions are commonly made that dynamical downscaling can resolve this issue. However, given the large magnitude of the biases in downscaled GCMs, it is unclear whether such projections are credible. Here, we use an ensemble of dynamically downscaled GCMs to evaluate this question in the Sierra‐Cascade mountain range of the western US. Future projections across this region are characterized by earlier seasonal shifts in peak flow, but with substantial inter‐model uncertainty (−25 ± 34.75 days, 95% confidence interval (CI)). We apply the emergent constraint (EC) method for the first time to dynamically downscaled projections, leading to a 39% (−28.25 ± 20.75 days, 95% CI) uncertainty reduction in future peak flow timing. While the constrained results can differ from bias corrected projections, the EC is based on GCM biases in historical peak flow timing and has a strong physical underpinning.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

Symmetry in auxiliary-field quantum Monte Carlo calculations

We show how symmetry properties can be used to greatly increase the accuracy and efficiency in auxiliary-field quantum Monte Carlo (AFQMC) calculations of electronic systems. With the Hubbard model as an example, we study symmetry preservation in two aspects of ground-state AFQMC calculations, the Hubbard-Stratonovich transformation and the form of the trial wave function. It is shown that significant improvement over state-of-the-art calculations can be achieved. In unconstrained calculations, the implementation of symmetry often leads to shorter convergence time and much smaller statistical errors and thereby a substantial reduction of the sign problem. Moreover, certain excited states become possible to calculate which are otherwise beyond reach. In calculations with constraints, the use of symmetry can reduce the systematic error from the constraint. It also allows release-constraint calculations, leading to essentially exact results in many cases. Detailed comparisons are made with exact diagonalization results. Accurate ground-state energies are then presented for larger system sizes in the two-dimensional repulsive Hubbard model.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Cognitive IoT and Edge Computing for Intrusion Detection with Federated TinyML

Internet of Things (IoT) and Edge Computing (EC) are rapidly becoming an integral part of the modern society. By 2030, there is estimated to be over 40 billion active and connected IoT devices [1]. This rapid progress also comes with a significant implication on cybersecurity. Back-end infrastructure and systems have a much broader attack than they did previously due to vulnerable IoT/EC devices being connected to wireless networks. This expanding attack surface is a growing concern because IoT/EC are increasingly being used in critical systems such as power grids, health care, and smart homes. To effectively address a problem of this scale, cognitive cyber methods—which can autonomously detect and react to cyber attacks as they develop—are needed. To address this, we bring Artificial Intelligence (AI) and Machine Learning (ML) to IoT/EC devices, using tinyML to monitor voluminous IoT data against cyber threats, and using Federated Learning (FL) to share local detection knowledge across the system while preserving privacy. We propose a novel three-layer architecture: (1) an IoT layer for tinyML-based inference, (2) an edge layer for ML model training, and (3) a cloud layer for FL operations. Using the publicly available 11-class N-BaIoT dataset [2], we demonstrate that this architecture mitigates resource constraints at the IoT layer while improving detection accuracy over standard two-layer designs. An outlier-resistant scaler, feature reduction, and quantization enable the tinyML model to maintain detection accuracy with a reduced model size. Additionally, federated learning that only utilizes the intersection (across heterogenous devices) of the reduced feature set achieves superior detection accuracy compared to locally trained models.

Li, Mingyan [ORNL] (ORCID:0009000569532640)↗

DOE OSTI2016

SU-F-T-501: Dosimetric Comparison of Single Arc-Per-Beam and Two Arc-Per-Beam VMAT Optimization in the Monaco Treatment Planning System

Purpose: The purpose of this study was to evaluate the dosimetric and practical effects of the Monaco treatment planning system “max arcs-per-beam” optimization parameter in pelvic radiotherapy treatments. Methods: A total of 17 previously treated patients were selected for this study with a range of pelvic disease site including prostate(9), bladder(1), uterus(3), rectum(3), and cervix(1). For each patient, two plans were generated, one using a arc-per-beam setting of ‘1’ and another with setting of ‘2’. The setting allows the optimizer to add a gantry direction change, creating multiple arc passes per beam sequence. Volumes and constraints established from the initial clinical treatments were used for planning. All constraints and dose coverage objects were kept the same between plans, and all plans were normalized to 99.7% to ensure 100% of the PTV received 95% of the prescription dose. We evaluated the PTV conformity index, homogeneity index, total monitor units, number of control points, and various dose volume histogram (DVH) points for statistical comparison (alpha=0.05). Results: We found for the 10 complex shaped target volumes (small central volumes with extending bilateral ‘arms’ to cover nodal regions) that the use of 2 arcs-per-beam achieved significantly lower average DVH values for the bladder V20 (p=0.036) and rectum V30 (p=0.001) while still meeting the high dose target constraints. DVH values for the simpler, more spherical PTVs were not found significantly different. Additionally, we found a beam delivery time reduction of approximately 25%. Conclusion: In summary, the dosimetric benefit, while moderate, was improved over a 1 arc-per-beam setting for complex PTVs, and equivalent in other cases. The overall reduced delivery time suggests that the use of multiple arcs-per-beam could lead to reduced patient on table time, increased clinical throughput, and reduced medical physics quality assurance effort.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1988

An improved V-Lambda solution of the matrix Riccati equation

The authors present an improved algorithm for computing the V-Lambda solution of the matrix Riccati equation. The improvement is in the reduction of the computational load, results from the orthogonality of the eigenvector matrix that has to be solved for. The orthogonality constraint reduces the number of independent parameters which define the matrix from n-squared to n (n - 1)/2. The authors show how to specify the parameters, how to solve for them and how to form from them the needed eigenvector matrix. In the search for suitable parameters, the analogy between the present problem and the problem of attitude determination is exploited, resulting in the choice of Rodrigues parameters.

Bar-Itzhack, Itzhack Y.↗

NASA NTRS1991

Maximum life spur gear design

Optimization procedures allow one to design a spur gear reduction for maximum life and other end use criteria. A modified feasible directions search algorithm permits a wide variety of inequality constraints and exact design requirements to be met with low sensitivity to initial guess values. The optimization algorithm is described, and the models for gear life and performance are presented. The algorithm is compact and has been programmed for execution on a desk top computer. Two examples are presented to illustrate the method and its application.

Savage, M.↗

NASA NTRS1991

Maximum life spur gear design

Savage, M.↗

NASA NTRS1992

The effect of helium diffusion on the ages of globular clusters

Evolutionary tracks for halo stars were calculated, and isochrones which include the effects of microscopic diffusion of helium were constructed. The isochrones were fitted to a metal poor (M92) and a moderately metal rich (NGC 288) globular cluster using an updated version of the Revised Yale Isochrone color calibration. Ages of the two clusters were also determined using the difference between the turnoff magnitude and horizontal branch magnitude, and the difference in color between the main-sequence turnoff and lower giant branch. Considering all methods and constraints, diffusion is argued to reduce the derived ages of M92 and NGC 288 by 0.5-1 Gyr. The maximum age reduction that diffusion could cause is 3 Gyr. Age estimates including diffusion indicate that M92 is 16 +/- 2 Gyr old, and that M92 is about 3 Gyr older than NGC 288, assuming that the clusters have the same O/Fe of +0.4.

Chaboyer, Brian↗

NASA NTRS1995

Practical aspects of variable reduction formulations and reduced basis algorithms in multidisciplinary design optimization

This paper discusses certain connections between nonlinear programming algorithms and the formulation of optimization problems for systems governed by state constraints. The major points of this paper are the detailed calculation of the sensitivities associated with different formulations of optimization problems and the identification of some useful relationships between different formulations. These relationships have practical consequences; if one uses a reduced basis nonlinear programming algorithm, then the implementations for the different formulations need only differ in a single step.

Lewis, Robert Michael↗

NASA NTRS1998

[Sources of Methane in the Boreal Region]

In determining the global methane budget the sources of methane must be balanced with the sinks and atmospheric inventory. The approximate contribution of the different methane sources to the budget has been establish showing the major terrestrial inputs as rice, wetlands, bogs, fens, and tundra. Measurements and modeling of production in these sources suggest that temperature, water table height and saturation along with substratum composition are important in controlling methane production and emission. The isotopic budget of 13 C and D/H in methane can be used as a tool to clarify the global budget. This approach has achieved success at constraining the inputs. Studies using the isotopic approach place constraints on global methane production from different sources. Also, the relation between the two biogenic production pathways, acetate fermentation and CO2 reduction, and the effect of substratum composition can be made using isotope measurements shows the relation between the different biogenic, thermogenic and anthropogenic sources of methane as a function of the carbon and hydrogen isotope values for each source and the atmosphere, tropospheric composition. Methane emissions from ponds and fens are a significant source in the methane budget of the boreal region. An initial study in 1993 and 1994 on the isotopic composition of this methane source and the isotopic composition in relation to oxidation of methane at the sediment surface of the ponds or fen was conducted as part of our BOREAS project. The isotopic composition of methane emitted by saturated anoxic sediment is dependent on the sediment composition and geochemistry, but will be influenced by in situ oxidation, in part, a function of rooted plant activity. The influence of oxidation mediated by rooted plant activities on the isotopic composition of methane is not well known and will depend on the plant type, sediment temperature, and numerous other variables. Information on this isotopic composition is important in both understanding the bio-geochemistry of the system and also in determining the regional and global inputs for the methane isotope budget. In determining the destruction of methane for balancing the atmospheric methane budget soil oxidation must be considered.

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