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At least 73 records · Page 4

Alignment-Insensitive Lower-Cost Telescope Architecture

This architecture features an active wavefront sensing and control scheme along with methods for measuring the relative positions of the primary to aft optics, such as the secondary mirror, and should enable larger and cheaper telescope architectures needed for future applications. A wavefront source/sensor is placed at the center of curvature of the primary mirror. The system provides continuous light onto a primary mirror that is retro-reflected onto itself. This allows the wavefront controller to constantly update the positions of the primary mirror segments (or deformable mirror actuators). Another function of this innovation involves using a concave mirror on the back of the secondary mirror (or other aft optic) that has the same center-of-curvature location (in defocus) as the primary mirror. The two return beams can be aligned next to each other on a detector, or radially on top of each other. This provides a means with which to measure the relative position of the primary to the secondary (or other aft optics), thus allowing for the removal of misalignment of the center-of-curvature source/sensor (meaning it doesn't need precision placement) and also provides a means with which to monitor the relative alignment over time. This innovation does not require extremely good thermal stability on the primary mirror and can thus be used in any thermal environment and with cheaper materials. In addition to this, the architecture lets one phase (or align) the primary mirror independent of whether a star or scene is in the field. The segmented, spherical primary allows for cost-effective three-meter class (e.g. Midex and Discovery) missions as well as enabling 30-meter telescope solutions that can be manufactured in a reasonable amount of time. The continuous wavefront sensing and control architecture enables missions for low-Earth-orbit.

Feinberg, Lee

Conceptual Feasibility Study of the Hyperloop Vehicle for Next-Generation Transport

The Hyperloop concept is proposed as a faster, cheaper alternative to high-speed rail and traditional short-haul aircraft. It consists of a passenger pod traveling through a tube under light vacuum while being propelled and levitated by a combination of permanent and electro-magnets. The concept addresses NASA's research thrusts for growth in demand, sustainability, and technology convergence for high-speed transport. Hyperloop is a radical departure from other advanced aviation concepts, however it remains an aeronautics concept that tackles the same strategic goals of low-carbon propulsion and ultra-effcient vehicles. System feasibility was investigated by building a multidisciplinary vehicle sizing model that takes into account aerodynamic, thermodynamic, structures, electromagnetic, weight, and mission analyses. The sizing process emphasized the strong coupling between the two largest systems: the tube and the passenger pod. The model was then exercised to examine Hyperloop from a technical and cost perspective. The structural sizing analysis of the travel tube demonstrates potential for signi cant capital cost reductions by considering an underwater route. Examination of varying passenger capacity indicates that the system can be operated with a wide range of passenger loads without significant change in operating expenses. Lastly, a high-level sizing study simulated variations in tube area, pressure, pod speed, and passenger capacity showing that there is a tube pressure that minimizes operating energy usage. The value of this optimal tube pressure is highly sensitive to numerous design details. These combined estimates of energy consumption, passenger throughput, and mission analyses all support Hyperloop as a faster and cheaper alternative to short-haul flights. The tools and expertise used to quantify these results also demonstrate how traditional aerospace design methods can be leveraged to handle the complex and coupled design process. Much of the technology development required for the Hyperloop is shared with next-generation aircraft. Furthermore, the substantial public interest and active commercial development make it an ideal candidate as an aircraft technology driver and test bed.

Hyperloop Vehicle

Online Multi-Modal Learning and Adaptive Information Trajectory Planning for Autonomous Exploration

In robotic information gathering missions, scientists are typically interested in understanding variables which require proxy measurements from specialized sensor suites to estimate. However, energy and time constraints limit how often these sensors can be used in a mission. Robots are also equipped with cheaper to use navigation sensors such as cameras. In this paper, we explore a challenging planning problem in which a robot is required to learn about a scientific variable of interest in an initially unknown environment by planning informative paths and deciding when and where to use its sensors. To tackle this we present two innovations: a Bayesian generative model framework to automatically learn correlations between expensive science sensors and cheaper to use navigation sensors online, and a sampling based approach to plan for multiple sensors while handling long horizons and budget constraints. Our approach does not grow in complexity with data and is anytime making it highly applicable to field robotics. We tested our approach extensively in simulation and validated it with real data collected during the 2014 Mojave Volatiles Prospector Mission. Our planning algorithm performs statistically significantly better than myopic approaches and at least as well as a coverage-based algorithm in an initially unknown environment while having added advantages of being able to exploit prior knowledge and handle other intricacies of the real world without further algorithmic modifications.

learning

Inserting new technology into small missions

Part of what makes small missions small is that they have less money. Executing missions at low cost implies extensive use of cost sharing with other missions or use of existing solutions. However, in order to create many small missions, new technology must be developed, applied, and assimilated. Luckily, there are methods for creating new technology and inserting it into faster-better-cheaper (FBC) missions.

technology infusion faster better cheaper

Mars Global Surveyor (MGS) High Temperature Survival Solar Array

The MGS mission is one of the first major palnetary missions conducted under the new NASA Faster, Better, Cheaper guidelines. This paper provides an overview of the array design and performance, the high temperature capable design and development.

Mars Global Surveyor MGS High Temperature Survival

Defect Detection and Prevention

As NASA continues to impement its Faster, Better, Cheaper philosophy, new approaches for implementing Mission Assurance activities are being developed.

faster

Transitory sensitivity in automatic chemical kinetic mechanism analysis

Abstract Detailed chemical kinetic mechanisms are necessary for resolving many important chemical processes. As the chemistry of smaller molecules has become better grounded and quantum chemistry calculations have become cheaper, kineticists have become interested in constructing progressively larger kinetic mechanisms to model increasingly complex chemical processes. These large kinetic mechanisms prove incredibly difficult to refine and time‐consuming to interpret. Traditional sensitivity analysis on a large mechanism can range from inconvenient to practically impossible without special techniques to reduce the computational cost. We first present a new time‐local sensitivity analysis we term transitory sensitivity analysis. Transitory sensitivity analysis is demonstrated in an example to accurately identify traditionally sensitive reactions at an 18,000x speed up over traditional sensitivities. By fusing transitory sensitivity analysis with more traditional time‐local branching, pathway, and cluster analyses, we develop an algorithm for efficient automatic mechanism analysis. This automatic mechanism analysis at a time point is able to identify the reactions a target is most sensitive to using transitory sensitivity analysis and then propose hypotheses why the reaction might be sensitive using branching, pathway, and cluster analyses. We implement these algorithms within the reaction mechanism simulator (RMS) package, which enables us to report the automatic mechanism analysis results in highly readable text formats and in molecular flux diagrams.

Johnson, Matthew S.

A multi‐variable framework for selecting WRF physics configurations at convection‐permitting scales: An Amazon wet‐season case study

Tropical convection over rainforests modulates atmospheric circulation and the energy and hydrological cycles across multiple scales. However, the scarcity of observations still limits our understanding of these processes. Although numerical models are utilized to investigate atmospheric physical processes, their performance depends on the choice of parameterizations and grid resolution. Here, in this work, we introduce and apply a multi‐variable, multi‐physics framework to evaluate and rank the Advanced Research Weather Research and Forecasting (WRF–ARW) configurations at 1‐km resolution over the central Amazon during the wet season. A 48‐member ensemble combines three land‐surface models (LSMs), four planetary boundary layer (PBL), and four microphysics (MP) schemes. Model performance for seven convection‐related near‐surface and boundary‐layer variables is assessed using Taylor diagrams and the Taylor skill score (TSS), analysis of variance (ANOVA)‐based sensitivity metrics, and non‐parametric rank tests. We then construct a combined, weighted TSS to identify configurations that are comparatively robust across variables. Results showed that most configurations reproduce near‐surface temperature, sensible and latent heat fluxes, and boundary‐layer height reasonably well, whereas humidity and rainfall remain challenging. LSM choice has the strongest impact on the surface fluxes and a secondary influence on near‐surface temperature and humidity, PBL schemes dominate boundary‐layer height, and MP schemes exert the largest control on rainfall. No single configuration is optimal for all variables, but the combination of Noah (LSM), Yonsei University (PBL), and Morrison (MP) emerges as the most robust configuration for this case, with the WRF single‐moment six‐class scheme (WSM6) providing a competitive, computationally cheaper MP alternative. The framework is general and can be applied to other regions, seasons, and convective regimes.

Amazon rainforest

Personalized and uncertainty-aware coronary hemodynamics simulations: From Bayesian estimation to improved multi-fidelity uncertainty quantification

Non-invasive simulations of coronary hemodynamics have improved clinical risk stratification and treatment outcomes for coronary artery disease, compared to relying on anatomical imaging alone. However, simulations typically use empirical approaches to distribute total coronary flow amongst the arteries in the coronary tree, which ignores patient variability, the presence of disease, and other clinical factors. Further, uncertainty in the clinical data often remains unaccounted for in the modeling pipeline. We present an end-to-end uncertainty-aware pipeline to (1) personalize coronary flow simulations by incorporating vessel-specific coronary flows as well as cardiac function; and (2) predict clinical and biomechanical quantities of interest with improved precision, while accounting for uncertainty in the clinical data. We assimilate patient-specific measurements of myocardial blood flow from clinical CT myocardial perfusion imaging to estimate branch-specific coronary artery flows. Simulated noise in the clinical data is used to estimate the joint posterior distributions of the model parameters using adaptive Markov Chain Monte Carlo sampling. Additionally, the posterior predictive distribution for the relevant quantities of interest is determined using a new approach combining multi-fidelity Monte Carlo estimation with non-linear, data-driven dimensionality reduction. This leads to improved correlations between high- and low-fidelity model outputs. Our framework accurately recapitulates clinically measured cardiac function as well as branch-specific coronary flows under measurement noise uncertainty. We observe substantial reductions in confidence intervals for estimated quantities of interest compared to single-fidelity Monte Carlo estimation and state-of-the-art multi-fidelity Monte Carlo methods. This holds especially true for quantities of interest that showed limited correlation between the low- and high-fidelity model predictions. In addition, the proposed multi-fidelity Monte Carlo estimators are significantly cheaper to compute than traditional estimators, under a specified confidence level or variance. The proposed pipeline for personalized and uncertainty-aware predictions of coronary hemodynamics is based on routine clinical measurements and recently developed techniques for CT myocardial perfusion imaging. The proposed pipeline offers significant improvements in precision and reduction in computational cost.

Bayesian parameter estimation

Supercritical water desalination and oxidation (SCWDO): Effectiveness on complex solutions, technoeconomic, and CO 2 impact for produced water treatment

The modern energy-economy is increasingly causing the production of highly saline brines, including from produced water. Supercritical water desalination can concentrate and extract minerals from these brines, but the effects of mixed salt interactions, organic degradation with additives, and the technology's economics are not well understood at supercritical condition. The present study evaluated and experimentally studied an integrated supercritical water desalination and oxidation (SCWDO) process for treating real-produced water samples from oil/natural gas field. The complex interactions between the various anions and cations in produced water were extensively evaluated. Most of the divalent and trivalent ions were extracted below 250 °C while the majority of the monovalent salt were removed between 380 to 410 °C. The treated real produced water was of drinking water quality, with <500 mg/l of total dissolved solid (TDS) and with 100% organics removal. Furthermore, the heat liberated during the organic oxidation could be utilized internally and for electricity generation for enhanced the energy efficiency and lower cost of produced water treatment. With system optimization, the proposed SCWDO process can essentially be made a net zero energy process. A novel process flow diagram for the commercial scale self-powered hybrid SCWDO technology was proposed as a cost-effective produced water treatment to mitigate the environmental crises. Techno-economic analysis showed that produced water treatment cost with SCWDO can be reduced to 2–3 $/m 3 and can be up to 60 % cheaper to traditional deep well reinjection. Additionally, the proposed SCWDO process could achieve net negative CO 2 emission.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Technoeconomic Analysis of Steel Production with Electric Thermal Energy Storage

The iron and steel industry is an important manufacturing sector and one of the largest energy consumers in the United States and globally. Hydrogen direct reduction of iron ore (H2DRI) is considered a promising process that could enhance domestic steel production. This process requires hydrogen inlet temperatures up to 950 degrees C to drive the endothermic reduction of the iron ore pellets. In this work we investigate the technoeconomic performance of an H2DRI plant using electric thermal energy storage (ETES) technologies for the hydrogen heating, compared to conventional natural gas fired heaters, hydrogen fired heaters, and electric hydrogen heaters. A technoeconomic analysis framework for the plant is developed and used in multiple case studies, covering different hydrogen prices, grid electricity profiles, and financing scenarios. The levelized cost of steel production is found out to be in the range of $775-950/mt, which is mostly inside the benchmarked steel price of $941/mt. ETES-based hydrogen heating is found to be in par with conventional natural gas fired heaters, and cheaper than hydrogen fired heaters and electric hydrogen heaters. The major cost drivers are the iron ore and hydrogen feedstock, followed by the hydrogen compression and heating capital. Several insights and suggested future directions are identified.

08 HYDROGEN

A comparative assessment of the economic viability of nuclear-integrated direct air capture systems

Direct air capture (DAC) systems require heat and electricity to operate, which can be supplied by nuclear power plants (NPPs). In this study, the performance and cost of various conceptual nuclear-DAC systems are assessed, and their performance is compared with several non-nuclear options. Three nuclear-DAC systems are considered: (1) a liquid solvent direct air capture (L-DAC) system with heat supplied from natural gas (NG) and electricity supplied by an NPP, (2) an electrified L-DAC system, fully powered by electricity from an NPP, and (3) a solid sorbent direct air capture (S-DAC) system utilizing both heat and electricity generated by an NPP. Two nuclear technologies are considered: a pressurized water reactor and a high-temperature gas-cooled reactor. Under the medium conservatism scenario, the levelized cost of direct air capture (LCOD) for these systems range from $\$$310/tCO 2 to $\$$525/tCO 2 with the L-DAC system having an NG heat supply at the lower end of the range, and the electrified L-DAC system and the S-DAC system at the higher end of the range. Coupling with nuclear energy led to a 21 % reduction in LCOD for the L-DAC system with NG heat supply and a 29 % reduction for the S-DAC system when compared to fully NG-powered options. When powering the DAC system with grid electricity, the LCOD is highly dependent on the assumed electricity price and carbon intensity. The nuclear option is the cheaper choice when the price of low-carbon grid electricity exceeds $\$$95/MWh and $\$$45/MWh for the L-DAC and S-DAC systems, respectively.

22 - GENERAL STUDIES OF NUCLEAR REACTORS

Enhanced performance of Bi 2 S 3 /TiO 2 heterostructure composite films for solar cell applications

Day to day energy production is shifting towards renewable energy sources as these sources become more economically viable while being less polluting to operate; solar energy has become one of the major sources of renewable energy. However, it currently relies on ultra-pure silicon ingots to produce commercial silicon photovoltaics, which prevents the cost of electricity being produced to compete with non-renewable energy production. A viable low-cost alternative for silicon based cells would be dye-sensitized solar cells (DSSCs), which are easier and cheaper to manufacture as they do not require expensive and delicate raw materials to make. Moreover, they could be made semi-flexible which allows for a greater variety of applications. A DSSC consists of three components, a photo-electrode, an electrolyte and a counter-electrode. When exposed to incident light, the complex photosensitizers in the photoelectrode release electrons which are transported to the external load, leaving the photoelectrode in an oxidized state. The electrons are collected by the counter electrode and used to reduce the electrolyte. This charged electrolyte then reduces the positively charged photoelectrode, allowing the process to begin again. To improve the efficiency of this process, we explore the use of bismuth sulfide (Bi 2 S 3 ) and titanium oxide (TiO 2 ) composite as photoelectrode material and investigate their impact on the efficiency of DSSC.

14 SOLAR ENERGY

A visco-plastic constitutive model for accurate densification and shape predictions in powder metallurgy hot isostatic pressing

Powder metallurgy hot isostatic pressing (PM-HIP) is an advanced manufacturing process that produces near net shape parts with high material utilization and uniform microstructures. Despite being used frequently to produce small-scale components, the application of PM-HIP to large-scale components is limited due to inadequate understanding of its complex mechanisms that cause unpredictable post-HIP shape distortions. A computational model can provide necessary information about the intermediate and final stages of the HIP process that can help understand it better and make accurate predictions. Generally, two types of computational models are employed for PM-HIP of metal powders, namely, plastic and visco-plastic models. Between these, the plastic model is preferred due to its cheaper calibration approach requiring less experimental data. However, the plastic model sometimes produces incorrect predictions when slight variations of the HIP conditions are encountered in practical situations. Therefore, this work presents a visco-plastic model that addresses these limitations of the plastic model. A novel modified calibration approach is employed for the visco-plastic model that utilizes less experimental data than existing approaches. With the new approach, the data requirement is same for both plastic and visco-plastic models. This also enables a quantitative comparison of plastic and visco-plastic models, which have been only qualitatively compared in the past. When calibrated with the same experimental data, both the models are found to produce similar results. In conclusion, the calibrated visco-plastic model is applied to several complex geometries, and the predictions are found to be in good agreement with experimental observations.

Hot isostatic pressing

>24% screen printed Cu contacted n-TOPCon solar cells with successful implementation of LECO process

In this paper, we report the successful fabrication of >24.0 % efficiency n-TOPCon Si solar cells with screen-printed, fire-through Cu contact to n-TOPCon on the rear side and Ag contacted boron emitter on the front side by implementing optimized firing and LECO conditions. The highest efficiency (24.3%) Cu contacted n-TOPCon cell in this study showed excellent cell performance parameters with V oc >730 mV, J sc of 41.1 mA/cm 2 and FF of 80.8%, resulting in an absolute efficiency gap of 0.2% between Cu-contacted and fully Ag contacted n-TOPCon cells (24.5%). The mini-module fabricated with the Cu contacted n-TOPCon cell showed excellent reliability and durability of open-circuit voltage (V oc ), pseudo fill factor (pFF) and efficiency after prolonged damp-heat tests. Such high efficiency screen printed Cu contacted n-TOPCon cells provide unique opportunity to replace very expensive Ag contact on n-TOPCon with cheaper screen printable Cu metal pastes.

14 SOLAR ENERGY

Nonunitary Variational Quantum Eigensolver with the Localized Active Space Method and Cost Mitigation

Accurately describing strongly correlated systems with affordable quantum resources remains a central challenge for quantum chemistry applications on near and intermediate term quantum computers. The localized active space self-consistent field (LASSCF) approximates the complete active space self-consistent field (CASSCF) by generating active space-based wave functions within specific fragments while treating interfragment correlation with mean-field approach, hence is computationally less expensive. Hardware-efficient ansatzes (HEA) offer affordable and shallower circuits, yet they often fail to capture the necessary correlation. Previously, Jastrow-factor-inspired nonunitary qubit operators were proposed to use with HEA for variational quantum eigensolver (VQE) calculations (so-called nuVQE), as they do not increase circuit depths and recover correlation beyond the mean-field level for Hartree–Fock initial states. Here, in this study, we explore running nuVQE with LASSCF as the initial state. The method, named LAS-nuVQE, is shown to recover interfragment correlations, reach chemical accuracy with a small number of gates (<70) in both H 4 and square cyclobutadiene (C 4 H 4 ), and produces more accurate energetics than its HEA counterparts at all circuit depths. To further address the inherent symmetry-breaking in HEA, we implemented spin-constrained LAS-nuVQE to extend the capabilities of HEA further and show spin-pure results for square cyclobutadiene. We also mitigate the increased measurement overhead of nuVQE via Pauli grouping and shot-frugal sampling, reducing measurement costs by up to 2 orders of magnitude compared to ungrouped operator, and show that one can achieve better accuracy with a small number of shots (10 3–4 ) per one expectation value calculation compared to noiseless simulations with one or two orders of magnitude more shots. Finally, wall clock time estimates show that, with our measurement mitigation protocols, nuVQE becomes a cheaper and more accurate alternative than vanilla VQE with HEA. Taken together, these developments illustrate a practical pathway toward performing multireference chemical simulations with accuracy and affordable resources on today’s quantum hardware, achieving both accuracy and affordability in challenging correlated systems.

Wang, Qiaohong [Univ. of Chicago, IL (United State

Degradation of Anion Exchange Membranes by Cation Elimination: Impact on Water Uptake, Nanostructure, and Ionic Mobility

Anion exchange membranes (AEMs) are an attractive platform for fuel cell and electrolysis technologies since they enable the use of cheaper, nonplatinum group metal electrodes and components. However, the widespread adoption of AEM-based devices is limited by chemical degradation of the AEM in the highly alkaline medium of operation. Experimental studies report three major pathways of degradation, including substitution (S N 2), elimination (E2), and backbone cleavage. The decline in membrane performance is likely due to a cumulative effect of several pathways, which has proven to be difficult to disentangle through experiments. Here we use coarse-grained molecular simulations to isolate the impact of E2 degradation, where cationic sites are replaced by an alkene group, on AEM water uptake, nanoscale morphology, structure of the ion-conducting channels, water mobility, and ionic conductivity. Our studies focus on the well-studied model AEM polyphenylene oxide with tetraalkylammonium cationic sites (PPO-TMA). We find that about half of the hydrophobic groups resulting from the degradation retract into the hydrophobic domains of the membrane. The reduction in ion exchange capacity (IEC) and the hydrophobicity of the alkene groups decrease both the equilibrium water uptake (%WU) and the number of water molecules per cation (λ) of the membrane. Interestingly, the evolution of λ with the IEC seems to follow that of undegraded PPO-TMA membranes. Additionally, we ascribe this to the similarity between the structure of the degraded monomer and the neutral one in the polymer. We conclude that most of the performance losses originate in the lower hydration of the degraded membrane.

36 MATERIALS SCIENCE