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DOE OSTI2013

Finite unified theories and their predicitions

All-loop Finite Unified Theories (FUTs) are very interesting N = 1 supersymmetric Grand Unified Theories (GUTs) realising an old field theory dream, and moreover have a remarkable predictive power due to the required reduction of couplings. The reduction of the dimensionless couplings in N = 1 GUTs is achieved by searching for renormalization group invariant (RGI) relations among them holding beyond the unification scale. Finiteness results from the fact that there exist RGI relations among dimensional couplings that guarantee the vanishing of all beta-functions in certain N = 1 GUTs even to all orders. Additional developments in the soft supersymmetry breaking sector of N = 1 GUTs and FUTs lead to exact RGI relations, i.e. reduction of couplings, in this dimensionful sector of the theory, too. Based on the above theoretical framework phenomenologically consistent FUTs have been constructed. Here we review two FUT models based on the SU(5) gauge group. Confronting their predictions with the top and bottom quark masses and other experimental constraints a light Higgs-boson mass in the range M{sub H} ∼ 121–126 GeV has been predicted, in striking agreement with the recent experimental results from ATLAS and CMS. Furthermore naturally a relatively heavy s-spectrum emerged with coloured supersymmetric particles above ∼1.5 TeV in agreement with the non-observation of those particles at the LHC. Restricting further the parameter space of the best version of the SU(5) FUT according to the reported accuracy of the Higgs boson mass and B-physics observables we find predictions for the rest of the Higgs masses and the s-spectrum.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1973

Data acquisition and reduction for the University of Virginia superconducting magnetic suspension and balance facility

The problems associated with data acquisition and reduction in the U.Va. superconducting magnetic suspension and balance facility are similar to those in free-flight ranges (or tunnels). The model undergoes a Quasi-six-degree of freedom motion which must be monitored both in position and angular orientation problem is made more difficult because geometric constraints prevent direct visual access to the model in the Mach 3 wind tunnel. The methods, accuracies and problems associated with the acquisition of data are discussed.

Jacobson, I. D.↗

NASA NTRS2002

Turbomachinery Airfoil Design Optimization Using Differential Evolution

An aerodynamic design optimization procedure that is based on a evolutionary algorithm known at Differential Evolution is described. Differential Evolution is a simple, fast, and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems, including highly nonlinear systems with discontinuities and multiple local optima. The method is combined with a Navier-Stokes solver that evaluates the various intermediate designs and provides inputs to the optimization procedure. An efficient constraint handling mechanism is also incorporated. Results are presented for the inverse design of a turbine airfoil from a modern jet engine and compared to earlier methods. The capability of the method to search large design spaces and obtain the optimal airfoils in an automatic fashion is demonstrated. Substantial reductions in the overall computing time requirements are achieved by using the algorithm in conjunction with neural networks.

Madavan, Nateri K.↗

DOE OSTI2017

Hippocampal dose from stereotactic radiosurgery for 4 to 10 brain metastases: Risk factors, feasibility of dose reduction via re-optimization, and patient outcomes

This study aimed to report hippocampal dose from single-fraction stereotactic radiosurgery (SRS) for 4 to 10 brain metastases and determine feasibility of hippocampal-sparing SRS. Patients with 4 to 10 brain metastases receiving single-isocenter, multi-target single-fraction SRS were identified. Hippocampi were contoured using the Radiation Therapy Oncology Group (RTOG) 0933 atlas. RTOG 0933 dose constraints were converted to a biologically effective dose using an alpha/beta of 2 (D{sub 100} 421 cGy, D{sub max} 665 cGy). Number of metastases, total target volume, prescribed dose, and distance of nearest metastasis (dmin) were analyzed as risk factors for exceeding hippocampal constraints. If hippocampi exceeded constraints, the SRS plan was re-optimized. Key dosimetric parameters were compared between original and re-optimized plans. To determine if a single target can exceed constraints, all targets but the closest metastasis were removed from the plan, and dosimetry was compared. Forty plans were identified. Fifteen hippocampi (19%) exceeded constraints in 12 SRS plans. Hippocampal sparing was achieved in 10 of 12 replanned cases (83%). Risk factors associated with exceeding hippocampal constraints were decreasing dmin (24.0 vs 8.0 mm, p = 0.002; odds ratio [OR] 1.14, 95% confidence interval [CI] 1.04 to 1.26) and total target volume (5.46 cm{sup 3}vs 1.98 cm{sup 3}, p = 0.03; OR 1.14, 95% CI 1.00 to 1.32). There was no difference in exceeding constraints for 4 to 5 vs 6 to 10 metastases (27% vs 21%, p = 0.409) or prescribed dose (18 Gy, p = 0.58). For re-optimized plans, there were no significant differences in planning target volume (PTV) coverage (99.6% vs 99.0%, p = 0.17) or conformality index (1.47 vs 1.4, p = 0.78). Six (50%) plans exceeded constraints with a single target. A substantial minority of hippocampi receive high radiation dose from SRS for 4 to 10 brain metastases. Decreasing distance of the closest metastasis and total target volume are associated with exceeding hippocampal constraints. Re-optimizing these plans yielded hippocampal-sparing SRS plans with acceptable dosimetry. Prospective evaluation of the impact of hippocampal dose from SRS on neurocognition merits consideration.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2022

Physics-informed regularization and structure preservation for learning stable reduced models from data with operator inference

Operator inference learns low-dimensional dynamical-system models with polynomial nonlinear terms from trajectories of high-dimensional physical systems (non-intrusive model reduction). Here, this work focuses on the large class of physical systems that can be well described by models with quadratic and cubic nonlinear terms and proposes a regularizer for operator inference that induces a stability bias onto learned models. The proposed regularizer is physics informed in the sense that it penalizes higher-order terms with large norms and so explicitly leverages the polynomial model form that is given by the underlying physics. This means that the proposed approach judiciously learns from data and physical insights combined, rather than from either data or physics alone. Additionally, a formulation of operator inference is proposed that enforces model constraints for preserving structure such as symmetry and definiteness in linear terms. Numerical results demonstrate that models learned with operator inference and the proposed regularizer and structure preservation are accurate and stable even in cases where using no regularization and Tikhonov regularization leads to models that are unstable.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1977

Configuration development study of the X-24C hypersonic research airplane, phase 3

The conclusion evolved from the three phased study on the configuration development of the X-24C Hypersonic Research Airplane makes it evident that it is practical to design and build the high performance National Hypersonic Flight Research Facility airplane with today's state of the art within the cost and operational constraints established by NASA. The vehicle launched at 31.75 Mg from the B-52 can cruise for 40 seconds at Mach 6.78 on scramjets. Without scramjets it can approach Mach 8 with a 453.6 Kg payload or do 70 seconds of cruise at Mach 6 with a 2.27 Mg payload. Reduction in cost is possible with a vehicle scaled to a lesser mass and capability.

Combs, H. G.↗

NASA NTRS1980

Discovery of optical molecular emission from the bipolar nebula surrounding HD 44179

Spectrophotometry and spectropolarimetry with HD 44179 are presented. These measurements reveal that the very broad bump evident in previous low-resolution spectra possesses a large amount of structure, including groups of narrow emission lines and several diffuse features. A reduction in polarization, but constant position angle, through the bump indicates that this emission originates within the nebula itself and merely dilutes the polarized scattered starlight. A few very weak atomic emission lines are detected, but the overall feature, which strongly resembles the emission spectra of some molecules, remains unidentified. Constraints on the excitation mechanism are discussed.

Schmidt, G. D.↗

NASA NTRS1984

The SIMRAND methodology - Simulation of Research and Development Projects

In research and development projects, a commonly occurring management decision is concerned with the optimum allocation of resources to achieve the project goals. Because of resource constraints, management has to make a decision regarding the set of proposed systems or tasks which should be undertaken. SIMRAND (Simulation of Research and Development Projects) is a methodology which was developed for aiding management in this decision. Attention is given to a problem description, aspects of model formulation, the reduction phase of the model solution, the simulation phase, and the evaluation phase. The implementation of the considered approach is illustrated with the aid of an example which involves a simplified network of the type used to determine the price of silicon solar cells.

Miles, R. F., Jr.↗

NASA NTRS1992

Recent advances in multidisciplinary optimization of rotorcraft

A joint activity involving NASA and Army researchers at NASA LaRC to develop optimization procedures to improve the rotor blade design process by integrating appropriate disciplines and accounting for all of the important interactions among the disciplines is described. The disciplines involved include rotor aerodynamics, rotor dynamics, rotor structures, airframe dynamics, and acoustics. The work is focused on combining these five key disciplines in an optimization procedure capable of designing a rotor system to satisfy multidisciplinary design requirements. Fundamental to the plan is a three-phased approach. In phase 1, the disciplines of blade dynamics, blade aerodynamics, and blade structure are closely coupled while acoustics and airframe dynamics are decoupled and are accounted for as effective constraints on the design for the first three disciplines. In phase 2, acoustics is integrated with the first three disciplines. Finally, in phase 3, airframe dynamics is integrated with the other four disciplines. Representative results from work performed to date are described. These include optimal placement of tuning masses for reduction of blade vibratory shear forces, integrated aerodynamic/dynamic optimization, and integrated aerodynamic/dynamic/structural optimization. Examples of validating procedures are described.

Adelman, Howard M.↗

NASA NTRS1992

Recent advances in integrated multidisciplinary optimization of rotorcraft

Adelman, Howard M.↗

NASA NTRS2017

Aeroelastic Wingbox Stiffener Topology Optimization

This work considers an aeroelastic wingbox model seeded with run-out blade stiffeners along the skins. Topology optimization is conducted within the shell webs of the stiffeners, in order to add cutouts and holes for mass reduction. This optimization is done with a global-local approach in order to moderate the computational cost: aeroelastic loads are computed at the wing-level, but the topology and sizing optimization is conducted at the panel-level. Each panel is optimized separately under stress, buckling, and adjacency constraints, and periodically reassembled to update the trimmed aeroelastic loads. The resulting topology is baselined against a design with standard full-depth solid stiffener blades, and found to weigh 7.43% less.

Stanford, Bret K.↗

NASA NTRS2020

Operational Techniques for Dealing with Long Eclipses During the MMS Extended Mission

Launch window design for the Magnetospheric Multiscale (MMS) mission ensured that no excessive eclipses would be encountered during the prime mission. However, no orbit solutions exist that satisfy the eclipse constraints indefinitely: most extended mission years contain 1-3 eclipses long enough to potentially damage either the spacecraft or its scientific instruments. Two steps were taken to improve the situation. Firstly, raising apogee radius from 25 to 29.34 Earth radii altered the Sun-Earth-MMS phasing, so efficiently achieving reductions in the long eclipse durations. These maneuvers were performed early this year, in preparation for the first pair of long eclipses in August 2019. Secondly, a set of operational steps were taken around the time of the eclipses to help maintain spacecraft and instrument temperatures while preventing power load shedding. These operational steps included raising key onboard temperatures through adjusting the spacecraft attitude to tilt the instrument deck towards the Sun, and engaging select heaters prior to going into eclipses. In addition, all scientific instruments were turned off, as well as high-power, non-critical spacecraft systems, to conserve energy.These steps each came with trade-offs which will be discussed in the paper. Finally, the results that were obtained when the spacecraft experienced the first extremely long eclipses will be discussed, as will lessons learned for future long eclipses.

Williams, Trevor↗

DOE OSTI2019

Assessment of algal biofuel resource potential in the United States with consideration of regional water stress

Algae have been considered as a promising feedstock for biofuels. Because scaling-up algae biofuels production consumes significant amount of water, the impact of water use should be considered. This study evaluates algae-derived biofuel production potential in the United States (US) with consideration of regional water stress. We identified 7,075 potential sites in the US meeting land, biomass productivity and CO2 co-locating criteria using the Biomass Assessment Tool (BAT). The impact of water use for algal biofuel production in terms of water scarcity footprint is quantified using modeled 33-year site-scale water consumption from BAT and the county-level water stress indicator from the Available Water Remaining for the US (AWARE-US) metric. Long-term (20 billion gallon per year [BGY]) and near-term (5 BGY) renewable diesel (RD) production targets are considered. To select suitable algae cultivation facilities, biomass yield and water use are considered with and without a water stress constraint. We found that ranking sites based on biomass yield results in a high water use impact (24.5 thousand US equivalent billion gallons (BGYe) for the long-term RD target). If sites are instead ranked on water use efficiency, water consumption is reduced on average by 62%, with an average reduction in biomass yield by 25%. To reconcile trade-offs between biomass yield and water use impact, AWARE-US can be applied along with considering biomass yield. This strategy removes sites located in water stressed areas while keeping high productivity sites. For the 20 BGY RD target, this reduces water use impact by 55% without lowering biomass productivity or 97% with moderate reductions (4% on average) in biomass productivity, compared to the sites ranked by biomass yield alone. The results demonstrate that incorporating water stress into energy-scale algae biofuel production planning is key to achieving synergies between biofuel yield and fresh water use impact.

09 BIOMASS FUELS↗

DOE OSTI2026

ClassNMSW- a real-time classification approach for non-recycled municipal solid waste using hyperspectral imaging

Real-time classification of non-recycled municipal solid waste (NMSW) is essential for efficient valorization. This study introduces ClassNMSW, a comprehensive framework for classifying 22 NMSW subclasses under industrial constraints by using hyperspectral imaging (HSI). A primary innovation of this work is the development of a variance-controlled spectral extraction algorithm. Unlike traditional methods that rely on simple averaging, this approach systematically investigates the extent of pixel extraction to minimize the loss of critical chemical information while maximizing data reduction thus ensuring high spectral fidelity with low computational cost. The approach developed in this work integrates automated, computer-vision-based background removal, eliminating the need for the manual thresholding common in current literature. To resolve ambiguities among chemically similar subclasses, a tiered classification and multi-camera fusion strategy (NIR17 and NIR22) is implemented. Results demonstrate that ClassNMSW achieves an object-wise weighted accuracy of 98.70% for single-sensor configurations and 100% under sensor fusion. A novel rolling-window strategy satisfies desired end-to-end latency of <2 s, satisfying the strict deterministic requirements of high-speed industrial sorting environments. The ClassNMSW framework provides a scalable foundation for advancing circularity and resource recovery in large-scale waste valorization operations.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2018

Hydrogen embrittlement in compositionally complex FeNiCoCrMn FCC solid solution alloy

The influence of internal hydrogen on the tensile properties of an equi-molar FeNiCoCrMn alloy results in a significant reduction of ductility, which is accompanied by a change in the fracture mode from ductile microvoid coalescence to intergranular failure. The introduction of 146.9 mass ppm of hydrogen reduced the plastic strain to failure from 0.67 in the uncharged case to 0.34 and 0.51 in hydrogen-charged specimens. This reduction in ductility and the transition in failure mode are clear indications that this alloy exhibits the classic signs of being susceptible to hydrogen embrittlement. The results are discussed in terms of the hydrogen-enhanced plasticity mechanism and its influence on hydrogen-induced intergranular failure. Furthermore, a new additional constraint that further promotes intergranular failure is introduced for the first time.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Understanding the Impacts of Biomass Blending on the Uncertainty of Hydrolyzed Sugar Yield from a Stochastic Perspective

Feedstock price and availability are key challenges for biorefinery development and biomass blending has been suggested as a route to overcome these limitations. However, the impacts of feedstock blending on the variability of yields of hydrolyzed sugar remained unclear. This study quantifies the uncertainties in the sugar yields from the blends of corn stover, switchgrass, and grass clippings by considering both variable and model uncertainties. The results indicate that feedstock blending reduces the uncertainties in sugar yields and delivers feedstock of more uniform quality. A further investigation on xxx demonstrates that the reduction in overall uncertainty is achieved by reduced compositional uncertainties of blended feedstock. Based on these results, the optimization of blending ratios was performed with respect to three objectives: (1) probability of meeting the sugar yield target; (2) expected sugar yields; and (3) sugar yield per unit feedstock expense, while satisfying constraints of feedstock availability and cost. In conclusion, the optimization method developed in this study, is readily applied to other combinations of feedstocks, biofuels production processes, and constraints.

09 BIOMASS FUELS↗

DOE OSTI2023

Isotope dependence of transport in ST40 hot ion mode plasmas

The ST40 compact, high-field spherical tokamak, operating at 2.1 T and with 1.8 MW of neutral beam heating, achieved central carbon impurity ion temperatures in excess of 10 keV, surpassing their business milestone of 100 M °C (8.6 keV). The high temperature discharges were in the hot ion mode, with $T_i \gg T_e$, and they were achieved in both hydrogen and deuterium plasmas with deuterium neutral beam injection. In order to achieve the high temperature scenarios, careful wall conditioning and scenario optimization was carried out in $H^0 \rightarrow H^+$, $D^0 \rightarrow H^+$, and finally in $D^0 \rightarrow D^+$ plasmas. The TRANSP transport code was employed to study the dependence of confinement and transport on isotopic mass, and the conditions that led to the high measured central ion temperatures in the $D^0 \rightarrow H^+$ and $D^0 \rightarrow D^+$ plasmas. The kinetic profiles input into TRANSP were inferred from line-of-sight and limited radial measurements as well as consistency with a number of other experimental constraints. The TRANSP results first showed that the main species central ion temperature was only 0.5–1 keV lower than the measured carbon impurity temperature, and thus in the high performance plasmas also surpassed the 100 M °C level. TRANSP also showed that while the electron thermal conduction loss was dominant, reductions in central ion transport, and an effective decoupling of the ions from the electrons, led to an increase in central ion temperatures with increasing plasma mass. In fact, the associated confinement times exhibited a strong dependence on the isotopic mass of the thermal plasma. These preliminary results are foundations for dedicated experiments with full kinetic profile measurements on ST40 in the next run campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Machine Learning to Select Experiments Driven by Fundamental Science and Applications for Targeted Nuclear Data Improvement

This work describes a blueprint for a process that accelerates progress in science by quantitatively answering the following question: What is the optimal combination of fundamental-science and application-driven experiments to maximally reduce pertinent data uncertainties? Answering this question entails solving a high-dimensional and complex optimization problem that is best solved with advanced statistic techniques often classified as machine learning. We apply this process within the framework of nuclear data with the aim to select an experiment combination that will reduce uncertainties in 239 Pu nuclear data for neutron energies between 1 and 600 keV. In this field, fundamental-physics driven data, called differential, look at one nuclear physics observable at a time. They are contrasted to application-driven, integral, data where one or few resulting values inform a broad set of nuclear data across several nuclides and energies. The candidates for integral experiments are criticality measurements that were refined by a genetic algorithm to be maximally sensitive to 239 Pu fission cross sections in the desired energy range. Twenty-three candidate differential experiments were investigated and span multiple nuclear physics observables (e.g., total, capture cross sections) for isotopes appearing in the integral experiments. The optimal combination among these candidate experiments was investigated via generalized least squares fitting, augmented with Gaussian processes to ameliorate statistical irregularities in data, and the D-optimality criterion. The latter evaluates for each pair of candidates the joint reduction in uncertainties of all 12200 nuclear data appearing in the integral experiments compared to the knowledge we have from 168 past experiments, theory, and nuclear data. We chose as differential measurements those that investigate 63 Cu and 239 Pu total cross sections, based on D-optimality rank and feasibility constraints. Two integral (criticality) experiments were selected: An experiment with Al 2 ⁢O 3 and graphite interleaved with Pu and a thick Cu reflector explores 1–30 keV, while we target the 30–600 keV range with an experiment that swaps boron in place of graphite with a different geometry.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗