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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Selective robust optimization: A new intensity-modulated proton therapy optimization strategy

Purpose: To develop a new robust optimization strategy for intensity-modulated proton therapy as an important step in translating robust proton treatment planning from research to clinical applications. Methods: In selective robust optimization, a worst-case-based robust optimization algorithm is extended, and terms of the objective function are selectively computed from either the worst-case dose or the nominal dose. Two lung cancer cases and one head and neck cancer case were used to demonstrate the practical significance of the proposed robust planning strategy. The lung cancer cases had minimal tumor motion less than 5 mm, and, for the demonstration of the methodology, are assumed to be static. Results: Selective robust optimization achieved robust clinical target volume (CTV) coverage and at the same time increased nominal planning target volume coverage to 95.8%, compared to the 84.6% coverage achieved with CTV-based robust optimization in one of the lung cases. In the other lung case, the maximum dose in selective robust optimization was lowered from a dose of 131.3% in the CTV-based robust optimization to 113.6%. Selective robust optimization provided robust CTV coverage in the head and neck case, and at the same time improved controls over isodose distribution so that clinical requirements may be readily met. Conclusions: Selective robust optimization may provide the flexibility and capability necessary for meeting various clinical requirements in addition to achieving the required plan robustness in practical proton treatment planning settings.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-EF-BRB-05: 4pi Non-Coplanar IMRT Beam Angle Selection by Convex Optimization with Group Sparsity Penalty

Purpose: Integrated beam orientation and fluence map optimization is expected to be the foundation of robust automated planning but existing heuristic methods do not promise global optimality. We aim to develop a new method for beam angle selection in 4π non-coplanar IMRT systems based on solving (globally) a single convex optimization problem, and to demonstrate the effectiveness of the method by comparison with a state of the art column generation method for 4π beam angle selection. Methods: The beam angle selection problem is formulated as a large scale convex fluence map optimization problem with an additional group sparsity term that encourages most candidate beams to be inactive. The optimization problem is solved using an accelerated first-order method, the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA). The beam angle selection and fluence map optimization algorithm is used to create non-coplanar 4π treatment plans for several cases (including head and neck, lung, and prostate cases) and the resulting treatment plans are compared with 4π treatment plans created using the column generation algorithm. Results: In our experiments the treatment plans created using the group sparsity method meet or exceed the dosimetric quality of plans created using the column generation algorithm, which was shown superior to clinical plans. Moreover, the group sparsity approach converges in about 3 minutes in these cases, as compared with runtimes of a few hours for the column generation method. Conclusion: This work demonstrates the first non-greedy approach to non-coplanar beam angle selection, based on convex optimization, for 4π IMRT systems. The method given here improves both treatment plan quality and runtime as compared with a state of the art column generation algorithm. When the group sparsity term is set to zero, we obtain an excellent method for fluence map optimization, useful when beam angles have already been selected. NIH R43CA183390, NIH R01CA188300, Varian Medical Systems; Part of this research took place while D. O’Connor was a summer intern at RefleXion Medical.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Poster - 32: Atlas Selection for Automated Segmentation of Pelvic CT for Prostate Radiotherapy

Atlas based-segmentation has recently been evaluated for use in prostate radiotherapy. In a typical approach, the essential step is the selection of an atlas from a database that the best matches of the target image. This work proposes an atlas selection strategy and evaluate it impacts on final segmentation accuracy. Several anatomical parameters were measured to indicate the overall prostate and body shape, all of these measurements obtained on CT images. A brute force procedure was first performed for a training dataset of 20 patients using image registration to pair subject with similar contours; each subject was served as a target image to which all reaming 19 images were affinity registered. The overlap between the prostate and femoral heads was quantified for each pair using the Dice Similarity Coefficient (DSC). Finally, an atlas selection procedure was designed; relying on the computation of a similarity score defined as a weighted sum of differences between the target and atlas subject anatomical measurement. The algorithm ability to predict the most similar atlas was excellent, achieving mean DSCs of 0.78 ± 0.07 and 0.90 ± 0.02 for the CTV and either femoral head. The proposed atlas selection yielded 0.72 ± 0.11 and 0.87 ± 0.03 for CTV and either femoral head. The DSC obtained with the proposed selection method were slightly lower than the maximum established using brute force, but this does not include potential improvements expected with deformable registration. The proposed atlas selection method provides reasonable segmentation accuracy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Selective Epitaxial Growth of III–N Structures Using Ion-Beam Nanolithography

The selective epitaxial growth of GaN by metalorganic vapor-phase epitaxy combined with ion-beam etching is investigated. To this end, partially masked GaN epitaxial layers are fabricated by depositing a thin Si{sub 3}N{sub 4} layer onto the surface in a single technological process with the growth of GaN and the subsequent opening of windows of different shapes in this layer by an ion beam. Selective epitaxial growth regimes are studied. It is shown that, in a situation where the total area of the windows in the mask is small relative to the total area of the sample, the required epitaxy duration should be 5–10 s, which impairs the reproducibility of the parameters of the epitaxial process. It is also shown that the mechanism of the selective growth of submicrometer objects differs significantly from that for planar layers and selectively grown layers with dimensions of ~1 μm or greater. The effect of precursor (trimethylgallium and ammonia) fluxes on the character of selective epitaxy is examined. To investigate the possibilities of varying mask topology for fabricating model objects with regard to photonic crystals, the impact of the shape and orientation of the windows in the Si{sub 3}N{sub 4} mask on the character of selective epitaxy is studied.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Exploring Deep Learning and Sparse Matrix Format Selection

We proposed to explore the use of Deep Neural Networks (DNN) for addressing the longstanding barriers. The recent rapid progress of DNN technology has created a large impact in many fields, which has significantly improved the prediction accuracy over traditional machine learning techniques in image classifications, speech recognitions, machine translations, and so on. To some degree, these tasks resemble the decision makings in many HPC tasks, including the aforementioned format selection for SpMV and linear solver selection. For instance, sparse matrix format selection is akin to image classification—such as, to tell whether an image contains a dog or a cat; in both problems, the right decisions are primarily determined by the spatial patterns of the elements in an input. For image classification, the patterns are of pixels, and for sparse matrix format selection, they are of non-zero elements. DNN could be naturally applied if we regard a sparse matrix as an image and the format selection or solver selection as classification problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Selective Electrochemical Capture and Release of Uranyl in Solution (Final Report)

The goal of this project is to investigate the selective, electrochemical capture and release of uranyl ((UO 2 ) 2 +) from biphasic or heterogeneous mixtures using a class of cluster molecules, ortho-carboranes (Cb), containing selective binding groups. Possible applications in PUREX, seawater uranyl extraction, or in actinide/lanthanide (An/Ln) or Ln/Ln separations are envisioned. With this funding, we sought to achieve these goals by harnessing the redox-switchable chelating properties of the “closo” Cb to the reduced “nido” Cb enabling the electrochemical control of the ligand bite angle. Using this premise, specific goals include: 1) integrating new selective coordinating groups (L) onto the carbon positions of Cb for the selective capture and release of uranyl, and; 2) anchoring these selective carboranes onto electrode and/or heterogeneous surfaces for the selective, heterogeneous capture and release of uranyl from aqueous solutions under flow conditions. Overall, this work focuses on advancing our understanding and controlling the properties of this new platform for metal capture and release chemistry which, we believe, has the potential for broader applicability in the separation sciences.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Understanding of catalytic transformation of shale gas and development of catalysts with high activity and selectivity through experimental exploration and theoretical simulation

Catalysis on transition metal oxides is equivalently important in contrast to that on metal catalysts in chemical and energy transformations. Understanding of catalytic reactions on early transition metal oxide catalysts is fundamentally intriguing and of great practical interest in efficient production of chemical and fuel feedstocks. Fundamental understanding of catalysis on transition metal oxide-based catalysts has been lagged behind catalysis on metals due to the complexity of chemistry and structure of surface and bulk of oxide catalysts and their structural flexibility in reactive environment at high temperatures. The funded DOE project explored surface chemistry of a few reducible oxides including CeO 2 - based, Co 3 O 4 -based, and CoO-based which are significant for heterogeneous catalysis. Through in-situ studies using ambient pressure X-ray photoelectron spectroscopy and high pressure scanning tunneling microscopy, we revealed phase transformation, the accompanying changes of surface chemistry and structure, and uncovered their correlations with catalytic activity and selectivity in catalytic reactions including reduction of NO with CO, water-gas shift, and chemical transformations of methane to methanol and acetic acid under mild conditions. Driven by the following two facts, we propose to pursue fundamental understanding of oxidative dehydrogenation of ethane and oxidative coupling of methane on oxide catalysts through both in-situ studies of catalyst surfaces during catalysis and computational studies in the renewal proposal. One driving force is the significance of oxidative dehydrogenation of ethane and oxidative coupling of methane for utilization of earth-abundant, relatively inexpensive energy resource and the urgent needs of efficient chemical processes to generate ethylene from shale gas. The other is that exploration of surface chemistry of oxide catalysts during catalysis has remained challenging though it is critical in deeply understanding catalysis on oxide catalysts and developing oxide-based catalysts toward high selectivity and activity. Therefore, the overall objective of the renewal proposal is to mechanistically understand the oxidative dehydrogenation of ethane and oxidative coupling of methane at a molecular level through building correlations between surface chemistry of catalysts during catalysis and the corresponding catalytic performances, and thus design catalysts with high selectivity and activity for production of ethylene with the guidance achieved from these fundamental studies. Experiments were designed to explore the influences of electronic states of cations supported on substrate oxides, cations of surface of the substrate oxides, and surface lattice oxygen atoms of the substrate oxides on their catalytic selectivity and activity. Surface chemistry, including oxidation state of the surface monomers and cations of substrate oxides and density of oxygen vacancies during catalysis, will be tracked with AP-XPS during catalysis. A correlation between surface chemistry of these catalysts at different temperatures and their corresponding catalytic selectivity for production of ethylene and activity will be built. Computational studies will calculate adsorption energies of reactant molecules and their dissociated species and intermediates on the catalyst surface, search transition states, and simulate reaction pathway close to experimental studies. By integrating the computational studies into these correlations to be built from experimental studies, fundamental understanding of the catalytic mechanisms of oxidative dehydrogenation of ethane and oxidative coupling of methane at a molecular level will be achieved. With these insights, new catalysts with high selectivity and activity will be developed.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Reconstruction and Selection of Neutrino Interactions in MicroBooNE using Deep Convolutional Neural Networks

In this document, we describe a new reconstruction workflow developed for the MicroBooNE experiment. It features the use of Deep Convolutional Neural Networks trained to recognize key structures within the data sufficient for the 3D reconstruction of neutrino interactions within the detector. As a test of the reconstruction utility, the products of the reconstruction workflow are used to select inclusive charged-current (CC) $\nu_e$ and $\nu_\mu$ interactions in both simulated and real MicroBooNE data. In simulation, our $\nu_e$ and $\nu_\mu$ selections achieve an efficiency of 57% and 68\%, respectively, with a purity of 91% and 96%, respectively. We find that these selections are competitive with the inclusive selections used for the most recent MicroBooNE LEE searches. In particular, the CC-$\nu_e$ inclusive selection efficiency improves by over 20% while also improving sample purity. As a first step in quantifying potential bias, the data and Monte Carlo expectati ons are compared for both selections using the MicroBooNE open data. Within statistical and systematic uncertainties, both the electron and muon CC-inclusive event samples agree. A comparison of the real data events chosen by our work and another reconstruction framework shows that the two analyses each identify a sizeable fraction of events the other does not. This suggests that future analyses integrating the strengths of each could lead to combined gains. This work demonstrates, for the first time on real LArTPC data, state-of-the-art neutrino interaction reconstruction centered around deep learning algorithms.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

A traits-based approach for prioritizing species for monitoring and surrogacy selection

The bar for justifying the use of vertebrate animals for study is being increasingly raised, thus requiring increased rigor for species selection and study design. Although we have power analyses to provide quantitative backing for the numbers of organisms used, quantitative backing for selection of study species is not frequently employed. This can be especially important when measuring the impacts of ecosystem alteration, when study species must be chosen that are both sensitive to the alteration and of sufficient abundance for study. Just as important is providing justification for designation of surrogate species for study, especially when the species of interest is rare or of conservation concern and selection of an appropriate surrogate can have legal implications. In this study, we use a combination of GIS, a fish traits database and multivariate statistical analyses to quantitatively prioritize species for study and to determine potential study surrogate species. We provide two case studies to illustrate our quantitative, traits-based approach for designating study species and surrogate species. In the first case study, we select broadly representative fish species to understand the effects of turbine passage on adult fishes based on traits that suggest sensitivity to turbine passage. In our second case study, we present a framework for selecting a surrogate species for an endangered species. Lastly, we suggest that our traits-based framework can provide quantitative backing and added justification to selection of study species while expanding the inference space of study results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Ethane-CO2 Mixture Adsorption in Silicalite: Influence of Tortuosity and Connectivity of Pores on Selectivity

Selective adsorption using nanoporous materials is an efficient strategy for separating gas mixtures. In a nanoporous material, pores can exist in different shapes and can have different degrees of inter-connectivity. In recent studies, both pore connectivity and tortuosity have been found to affect the adsorption and dynamical properties of ethane and CO2 in silicalite differently. Here, using Monte Carlo simulations, we investigate if these two attributes can affect the selective adsorption of one component from a mixture of ethane and CO2 in silicalite. For this, the adsorption of an equimolar mixture of ethane and CO2 is simulated in 12 models of silicalite—SnZm (n, m = 0, 1, 2, 3 or 4; with n and m denoting, respectively, the fraction (out of 4) of straight and zigzag channels of silicalite that are available for adsorption)—differing in degrees of pore connectivity and tortuosity. The adsorption selectivity in this system is found to exhibit a reversal with the adsorption dominated by ethane at low pressures (below ~1 atm) and by CO2 at higher pressures (above ~10 atm). Pore connectivity is found to suppress the selective adsorption of CO2 at higher pressures and also shifts the selectivity reversal to higher pressures. The selectivity reversal results from a competition between the polarizability-affected adsorption at lower pressures and efficient packing at higher pressures. The efficient packing of CO2 is a compounded effect resulting from the larger effective pore volume available for CO2 due to its stronger interaction with the pore surface and smaller molecular volume. CO2 molecules show a preference to adsorb in non-tortuous pores, and this preference is found to be stronger in the presence of ethane. The effects of pore connectivity and tortuosity elucidated here should be applicable to a wide range of natural and engineered nanoporous materials, and this knowledge could be used to identify materials with better capability for separating and storing CO2 based on their pore attributes.

Gautam, Siddharth (ORCID:0000000314435382)↗
DOE OSTI2016

Investigating the impact of optical selection effects on observed rest-frame prompt GRB properties

Measuring gamma-ray burst (GRB) properties in their rest frame is crucial for understanding the physics at work in GRBs. This can only be done for GRBs with known redshifts. Since redshifts are usually measured from the optical spectrum of the afterglow, correlations between prompt and afterglow emissions may introduce biases into the distribution of the rest-frame properties of the prompt emission, especially considering that we measure the redshift of only one-third of Swift GRBs. In this paper, we study the optical flux of GRB afterglows and its connection to various intrinsic properties of GRBs. We also discuss the impact of the optical selection effect on the distribution of rest-frame prompt properties of GRBs. Our analysis is based on a sample of 90 GRBs with good optical follow-up and well-measured prompt emission. Seventy-six of them have a measure of redshift and 14 have no redshift. We compare the rest-frame prompt properties of GRBs with different afterglow optical fluxes in order to check for possible correlations between the promt properties and the optical flux of the afterglow. The optical flux is measured two hours after the trigger, which is a typical time for the measure of the redshift. We find that the optical flux of GRB afterglows in our sample is mainly driven by their optical luminosity and depends only slightly on their redshift. We show that GRBs with low and high afterglow optical fluxes have similar E {sub pi}, E {sub iso}, and L {sub iso}, indicating that the rest-frame distributions computed from GRBs with a redshift are not significantly distorted by optical selection effects. However, we found that the T{sub 90}{sup rest} distribution is not immune to optical selection effects, which favor the selection of GRBs with longer durations. Finally, we note that GRBs well above the E {sub pi}–E {sub iso} relation have lower optical fluxes and we show that optical selection effects favor the detection of GRBs with bright optical afterglows located close to or below the best-fit E {sub pi}–E {sub iso} relation (Amati relation), whose redshift is easily measurable. With more than 300 GRBs with a redshift, we now have a much better view of the intrinsic properties of these remarkable events. At the same time, increasing statistics allow us to understand the biases acting on the measurements. The optical selection effects induced by the redshift measurement strategies cannot be neglected when we study the properties of GRBs in their rest frame, even for studies focused on prompt emission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Discovery of 16 New z ∼ 5.5 Quasars: Filling in the Redshift Gap of Quasar Color Selection

We present initial results from the first systematic survey of luminous z ∼ 5.5 quasars. Quasars at z ∼ 5.5, the post-reionization epoch, are crucial tools to explore the evolution of intergalactic medium, quasar evolution, and the early super-massive black hole growth. However, it has been very challenging to select quasars at redshifts 5.3 ≤ z ≤ 5.7 using conventional color selections, due to their similar optical colors to late-type stars, especially M dwarfs, resulting in a glaring redshift gap in quasar redshift distributions. We develop a new selection technique for z ∼ 5.5 quasars based on optical, near-IR, and mid-IR photometric data from Sloan Digital Sky Survey (SDSS), UKIRT InfraRed Deep Sky Surveys—Large Area Survey (ULAS), VISTA Hemisphere Survey (VHS), and Wide Field Infrared Survey Explorer . From our pilot observations in the SDSS-ULAS/VHS area, we have discovered 15 new quasars at 5.3 ≤ z ≤ 5.7 and 6 new lower redshift quasars, with SDSS z band magnitude brighter than 20.5. Including other two z ∼ 5.5 quasars already published in our previous work, we now construct a uniform quasar sample at 5.3 ≤ z ≤ 5.7, with 17 quasars in a ∼4800 square degree survey area. For further application in a larger survey area, we apply our selection pipeline to do a test selection by using the new wide field J-band photometric data from a preliminary version of the UKIRT Hemisphere Survey (UHS). We successfully discover the first UHS selected z ∼ 5.5 quasar.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2001

Assembly For Moving a Robotic Device Along Selected Axes

An assembly for moving a robotic device along selected axes includes a programmable logic controller (PLC) for controlling movement of the device along selected axes to effect movement of the device to a selected disposition. The PLC includes a plurality of single axis motion control modules, and a central processing unit (CPU) in communication with the motion control modules. A human-machine interface is provided for operator selection of configurations of device movements and is in communication with the CPU. A motor drive is in communication with each of the motion control modules and is operable to effect movement of the device along the selected axes to obtain movement of the device to the selected disposition.

Brentley Craig Nowlin↗
NASA NTRS2004

Selection of an Alternate Biocide for the ISS Internal Thermal Control System Coolant, Phase 2

The ISS (International Space Station) ITCS (Internal Thermal Control System) includes two internal coolant loops that utilize an aqueous based coolant for heat transfer. A silver salt biocide had previously been utilized as an additive in the coolant formulation to control the growth and proliferation of microorganisms within the coolant loops. Ground-based and in-flight testing demonstrated that the silver salt was rapidly depleted, and did not act as an effective long-term biocide. Efforts to select an optimal alternate biocide for the ITCS coolant application have been underway and are now in the final stages. An extensive evaluation of biocides was conducted to down-select to several candidates for test trials and was reported on previously. Criteria for that down-select included: the need for safe, non-intrusive implementation and operation in a functioning system; the ability to control existing planktonic and biofilm residing microorganisms; a negligible impact on system-wetted materials of construction; and a negligible reactivity with existing coolant additives. Candidate testing to provide data for the selection of an optimal alternate biocide is now in the final stages. That testing has included rapid biocide effectiveness screening using Biolog MT2 plates to determine minimum inhibitory concentration (amount that will inhibit visible growth of microorganisms), time kill studies to determine the exposure time required to completely eliminate organism growth, materials compatibility exposure evaluations, coolant compatibility studies, and bench-top simulated coolant testing. This paper reports the current status of the effort to select an alternate biocide for the ISS ITCS coolant. The results of various test results to select the optimal candidate are presented.

Wilson, Mark E.↗
NASA NTRS2009

A Systematic Approach to Sensor Selection for Aircraft Engine Health Estimation

A systematic approach for selecting an optimal suite of sensors for on-board aircraft gas turbine engine health estimation is presented. The methodology optimally chooses the engine sensor suite and the model tuning parameter vector to minimize the Kalman filter mean squared estimation error in the engine s health parameters or other unmeasured engine outputs. This technique specifically addresses the underdetermined estimation problem where there are more unknown system health parameters representing degradation than available sensor measurements. This paper presents the theoretical estimation error equations, and describes the optimization approach that is applied to select the sensors and model tuning parameters to minimize these errors. Two different model tuning parameter vector selection approaches are evaluated: the conventional approach of selecting a subset of health parameters to serve as the tuning parameters, and an alternative approach that selects tuning parameters as a linear combination of all health parameters. Results from the application of the technique to an aircraft engine simulation are presented, and compared to those from an alternative sensor selection strategy.

Simon, Donald L.↗
NASA NTRS2011

Two Catalysts for Selective Oxidation of Contaminant Gases

Two catalysts for the selective oxidation of trace amounts of contaminant gases in air have been developed for use aboard the International Space Station. These catalysts might also be useful for reducing concentrations of fumes in terrestrial industrial facilities especially facilities that use halocarbons as solvents, refrigerant liquids, and foaming agents, as well as facilities that generate or utilize ammonia. The first catalyst is of the supported-precious-metal type. This catalyst is highly active for the oxidation of halocarbons, hydrocarbons, and oxygenates at low concentrations in air. This catalyst is more active for the oxidation of hydrocarbons and halocarbons than are competing catalysts developed in recent years. This catalyst completely converts these airborne contaminant gases to carbon dioxide, water, and mineral acids that can be easily removed from the air, and does not make any chlorine gas in the process. The catalyst is thermally stable and is not poisoned by chlorine or fluorine atoms produced on its surface during the destruction of a halocarbon. In addition, the catalyst can selectively oxidize ammonia to nitrogen at a temperature between 200 and 260 C, without making nitrogen oxides, which are toxic. The temperature of 260 C is higher than the operational temperature of any other precious-metal catalyst that can selectively oxidize ammonia. The purpose of the platinum in this catalyst is to oxidize hydrocarbons and to ensure that the oxidation of halocarbons goes to completion. However, the platinum exhibits little or no activity for initiating the destruction of halocarbons. Instead, the attack on the halocarbons is initiated by the support. The support also provides a high surface area for exposure of the platinum. Moreover, the support resists deactivation or destruction by halogens released during the destruction of halocarbons. The second catalyst is of the supported- metal-oxide type. This catalyst can selectively oxidize ammonia to nitrogen at temperatures up to 400 C, without producing nitrogen oxides. This catalyst converts ammonia completely to nitrogen, even when the concentration of ammonia is very low. No other catalyst is known to oxidize ammonia selectively at such a high temperature and low concentration. Both the metal oxide and the support contribute to the activity and selectivity of this catalyst.

Wright, John D.↗
NASA NTRS2020

Orbit Selection for the Proposed Lynx Observatory Mission

The Advanced Concepts Office design team performed several analyses and trades in support of orbit selection for the proposed Lynx mission, an x-ray observatory being submitted to the Astro2020 Decadal Survey. Though the descriptions in this Technical Memorandum (TM) focus on the Lynx mission, the approach and process for selecting the final orbit is applicable to a variety of proposed science and exploration missions. To select the best orbit for the Lynx science, mission designers assembled a team of subsystem and discipline experts, in addition to mission analysts, to evaluate several candidate orbits. These discipline experts included members of the science and instrument team, power and avionics, thermal, propulsion, and environments. The goal was to clearly show the benefits and weaknesses of each orbit in the trade space and provide sound justification for the final selection. Discipline experts conducted trades and evaluated the results using a variety of methods including engineering judgement, rough estimates, and detailed calculations, and rolled the results into a final grade using a weighted grading method. The orbit options could then be ranked. The principal investigator (PI) for the mission, along with the science team, was given the task of final orbit selection. The result of the trades indicated that a halo orbit about the second Sun-Earth Lagrange point (SE-L2), similar to the planned orbit for the James Webb Space Telescope (JWST), was the best choice for the Lynx mission. Details of how the team arrived at this selection are below.

Hopkins, R. C.↗
NASA NTRSDate not supplied

Motor Configuration Selection for A New Technical Challenge to Develop A 5 MW Cryogenic Motor and Drive

Due to aviation’s appreciable and growing share of humanity’s impact on our environment and estimates that CO2emissions only account for 34% of aviation’s total effective radiative forcing [1], there is a need to reach beyond climate goals that focus only on CO2emissions, such as the US Aviation Climate Action Plan’s [3] goal to reach net-zero carbon emissions by 2050.There is motivation to develop technology that pushes toward future large transport aircraft with net zero climate impact that are highly electrified (i.e., have higher power electrical propulsion system components). This paper describes a new, 6-year technical challenge to address this need by developing a 5 MW superconducting motor and cryogenic drive. Section 1 will detail the motivation for this work. Section 2 will describe the technical challenge and the selected specifications for the motor. Section 3 will present the results of a motor configuration trade study and the down selection of one configuration to develop a detailed design for. The technical challenge focuses on the design of a5 MW superconducting motor and cryogenic drive and demonstration of it at a 2+ MW scale to achieve TRL 3. Both fully superconducting (superconducting stator and rotor) and fully cryogenic (superconducting rotor and cryogenic stator) machine configurations will be explored. An emphasis will be placed on addressing the key tall poles for high power superconducting machines. Further details will be included in the full paper. The requirements and goals of the motor will be detailed. The rated speed (2,000 to 3,000 rpm) is defined to be appropriate for directly driving multi-MW fans or propellers. A range of rated speed is permitted because the motor is not designed for a specific aircraft and to provide design flexibility if AC losses in the stator winding are found to be a significant constraint (i.e., a lower speed can be selected to reduce electrical frequency). Relatively conservative requirements for efficiency (99%) and specific power (20 kW/kg) are defined, because TRL advancement and pushing toward flight readiness is emphasized over performance optimization. However, more aggressive efficiency and specific power goals are specified (99.9% and 40 kW/kg). The 3rd section will present the results of a motor configuration trade study. The study started with a qualitative assessment of sixteen motor configurations based on geometric, mechanical, thermal, and electromagnetic criteria. This assessment has been completed with three evaluators scoring all nine criteria. A configuration down select was made by prioritizing the sixteen configurations into four tiers based on each configuration’s total score and consideration of manufacturability, complexity, and support hardware (e.g., rotary vacuum seals, bearings). Configurations in priority A and B will be further evaluated through quantitative assessments, whereas those in priority C will only be further evaluated if time permits and priority D will not be further evaluated. Eight of the sixteen configurations were down selected for quantitative assessment, which will include analytical calculations and low-to moderate-fidelity finite element analysis to produce a preliminary Pareto front of efficiency versus specific power for each configuration. This assessment emphasizes the calculation of AC losses in the stator winding and an exploration of thermal management approaches to remove that heat and maintain cryogenic temperature. The final paper will include a description of each motor configuration that was considered. The quantitative assessments are underway, and an assessment of one configuration is complete for multiple stator conductor options. The remaining assessments are scheduled to be completed by late March so that the final down select to one configuration can be included in this paper.

Net Zero↗