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At least 703 records · Page 39

Lens alignment system and method

A lens alignment system and method is disclosed. The disclosed system/method integrates one or more lens retaining members/tubes (LRM/LRT) and focal length spacers (FLS) each comprising a metallic material product (MMP) specifically manufactured to have a thermal expansion coefficient (TEC) in a predetermined range via selection of the individual MMP materials and an associated MMP manufacturing process providing for controlled TEC. This controlled LRM/LRT TEC enables a plurality of optical lenses (POL) fixed along a common optical axis (COA) by the LRM/LRT to maintain precise interspatial alignment characteristics that ensure consistent and/or controlled series focal length (SFL) within the POL to generate a thermally neutral optical system (TNOS). Integration of the POL using this LRM/LRT/FLS lens alignment system reduces the overall TNOS implementation cost, reduces the overall TNOS mass, reduces TNOS parts component count, and increases the reliability of the overall optical system.

Monroe, James Alan↗

Sparse-grid discontinuous Galerkin methods for the Vlasov–Poisson–Lenard–Bernstein model

Sparse-grid methods have recently gained interest in reducing the computational cost of solving high-dimensional kinetic equations. In this paper, we construct adaptive and hybrid sparse-grid methods for the Vlasov–Poisson–Lenard–Bernstein (VPLB) model. This model has applications to plasma physics and is simulated in two reduced geometries: a 0x3v space homogeneous geometry and a 1x3v slab geometry. Here we use the discontinuous Galerkin (DG) method as a base discretization due to its high-order accuracy and ability to preserve important structural properties of partial differential equations. We utilize a multiwavelet basis expansion to determine the sparse-grid basis and the adaptive mesh criteria. We analyze the proposed sparse-grid methods on a suite of three test problems by computing the savings afforded by sparse-grids in comparison to standard solutions of the DG method. The results are obtained using the adaptive sparse-grid discretization library ASGarD.

97 MATHEMATICS AND COMPUTING↗

Recent Changes in High-Latitude Glaciers, Ice Caps, and Ice Sheets

The glaciers and ice sheets of the world contain enough ice to raise sea level by approximately 70 meters if they were to disappear entirely, and most of this ice is located in the climatically sensitive polar regions. Fortunately changes of this magnitude would probably take many thousands of years to occur, but recent discoveries indicate that these ice masses are responding to changes in today s climate more rapidly than previously thought. These responses are likely to be of great societal significance, primarily in terms of their implications for sea level, but also in terms of how their discharge of freshwater, through melting or calving, may impact ocean circulation. For millions of years, oceans have risen and fallen as the Earth has warmed and cooled, and ice on land has shrunk and grown. Today is no different in that respect, as sea levels have been rising at a rate of nearly 2 m per year during the last century (Miller and Douglas 2004), and 3 mm/yr in the last 12 years (Leuliette et al. 2004). What is different today, however, is that tens - perhaps hundreds - of millions of people live in coastal areas that are vulnerable to changes in sea level. Rising seas erode beaches, increase flood potential, and reduce the ability of barrier islands and coastal wetlands to mitigate the effects of major storms and hurricanes. The costs associated with a one-meter rise in sea level are estimated to be in the hundreds of billions of dollars in the United States alone. The worldwide costs in human terms would be far greater as some vulnerable low-lying coastal regions would become inundated, especially in poorer nations that do not have the resources to deal with such changes. Such considerations are particularly important in light of the fact that a one meter sea level rise is not significantly outside the 0.09 to 0.88 range of predictions for this century (IPCC 2001), and rises of this magnitude have occurred in the past in as little as 20 years (Fairbanks 1989). While the expansion of the warming oceans is estimated to be about a third of recent sea level rise, (Miller and Douglas 2004) the greatest potential for significantly increasing sea level lies in the Greenland and Antarctic ice sheets. For different reasons, each exhibits characteristics that suggest they are potentially unstable. In Antarctica, large portions of the ice cover rest on a soft bed that lies below sea level, making it vulnerable to runaway retreat. The Greenland ice sheet experiences considerable melt, which has the potential to rapidly accelerate the flow of ice toward the sea. While smaller ice masses, such as the Alaskan Glaciers and the Canadian ice caps, do not have anywhere near the same potential to impact sea level as the vast ice sheets do, many are melting rapidly, posing a significant near-term threat.

Abdalati, Waleed↗

Real-space density kernel method for Kohn–Sham density functional theory calculations at high temperature

Kohn–Sham density functional theory calculations using conventional diagonalization based methods become increasingly expensive as temperature increases due to the need to compute increasing numbers of partially occupied states. In this work, we present a density matrix based method for Kohn–Sham calculations at high temperatures that eliminates the need for diagonalization entirely, thus reducing the cost of such calculations significantly. Specifically, we develop real-space expressions for the electron density, electronic free energy, Hellmann–Feynman forces, and Hellmann–Feynman stress tensor in terms of an orthonormal auxiliary orbital basis and its density kernel transform, the density kernel being the matrix representation of the density operator in the auxiliary basis. Using Chebyshev filtering to generate the auxiliary basis, we next develop an approach akin to Clenshaw–Curtis spectral quadrature to calculate the individual columns of the density kernel based on the Fermi operator expansion in Chebyshev polynomials and employ a similar approach to evaluate band structure and entropic energy components. We implement the proposed formulation in the SPARC electronic structure code, using which we show systematic convergence of the aforementioned quantities to exact diagonalization results, and obtain significant speedups relative to conventional diagonalization based methods. Finally, we employ the new method to compute the self-diffusion coefficient and viscosity of aluminum at 116 045 K from Kohn–Sham quantum molecular dynamics, where we find agreement with previous more approximate orbital-free density functional methods.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Identifying Robust Decarbonization Pathways for the Western U.S. Electric Power System Under Deep Climate Uncertainty

Climate change threatens the resource adequacy of future power systems. Existing research and practice lack frameworks for identifying decarbonization pathways that are robust to climate-related uncertainty. We create such an analytical framework, then use it to assess the robustness of alternative pathways to achieving 60% emissions reductions from 2022 levels by 2040 for the Western U.S. power system. Our framework integrates power system planning and resource adequacy models with 100 climate realizations from a large climate ensemble. Climate realizations drive electricity demand; thermal plant availability; and wind, solar, and hydropower generation. Among five initial decarbonization pathways, all exhibit modest to significant resource adequacy failures under climate realizations in 2040, but certain pathways experience significantly less resource adequacy failures at little additional cost relative to other pathways. By identifying and planning for an extreme climate realization that drives the largest resource adequacy failures across our pathways, we produce a new decarbonization pathway that has no resource adequacy failures under any climate realizations. This new pathway is roughly 5% more expensive than other pathways due to greater capacity investment, and shifts investment from wind to solar and natural gas generators. Our analysis suggests modest increases in investment costs can add significant robustness against climate change in decarbonizing power systems. Our framework can help power system planners adapt to climate change by stress testing future plans to potential climate realizations, and offers a unique bridge between energy system and climate modeling.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A Physics-Constrained Deep Learning Model for Simulating Multiphase Flow in 3D Heterogeneous Porous Media

Physics-based simulators for multiphase flow in porous media emulate nonlinear processes with coupled physics, and usually require extensive computational resources for software development, maintenance and simulation execution. As a result, a huge demand exists for fast modeling of coupled processes in a wide range of subsurface applications including geological sequestration, hydrocarbon recovery and geothermal energy extraction. In this work, an efficient physics-constrained deep learning model is developed for solving multiphase flow in 3-Dimensional (3D) heterogeneous porous media. The model fully leverages the spatial topology predictive capability of convolutional neural networks, specifically U-Net with successive contracting and expansive steps, and is coupled with an efficient continuity-based smoother to predict flow responses that need spatial continuity. Furthermore, the transient regions are penalized to steer the training process such that the model can accurately capture flow in these regions. The model takes inputs including properties of porous media, fluid properties and well controls, and predicts the temporal-spatial evolution of the state variables (pressure and saturation). While maintaining the continuity of fluid flow, the 3D spatial domain is decomposed into 2D images for reducing training cost, and the decomposition results in an increased number of training data samples and better training efficiency. Additionally, a surrogate model is separately constructed as a postprocessor to calculate well flow rate based on the predictions of state variables from the deep learning model. We use the example of CO 2 injection into saline aquifers, and apply the physics-constrained deep learning model that is trained from physics-based simulation data and emulates the physics process. The model performs prediction with a speedup of ~ 1400 times compared to physics-based simulations, and the average temporal errors of predicted pressure and saturation plumes are 0.27% and 0.099% respectively. Furthermore, water production rate is efficiently predicted by a surrogate model for well flow rate, with a mean error less than 5%. Therefore, with its unique scheme to cope with the fidelity in fluid flow in porous media, the physics-constrained deep learning model can become an efficient predictive model for computationally demanding inverse problems or other coupled processes.

58 GEOSCIENCES↗

Time-dependent orbital-free density functional theory: Background and Pauli kernel approximations

Time-dependent orbital-free density functional theory (DFT) is an efficient method for calculating the dynamic properties of large-scale quantum systems due to the low computational cost compared to standard time-dependent DFT. In this work, we formalize this method by mapping the real system of interacting fermions onto a fictitious system of noninteracting bosons. The dynamic Pauli potential and associated kernel emerge as key ingredients of time-dependent orbital-free DFT. Using the uniform electron gas as a model system, we derive an approximate frequency-dependent Pauli kernel. Pilot calculations suggest that space nonlocality is a key feature for this kernel. Nonlocal terms arise already in the second-order expansion with respect to unitless frequency and reciprocal space variable ($\frac{ω}{qk_F}$ and $\frac{q}{2k_F}$, respectively). Given the encouraging performance of the proposed kernel, we expect it will lead to more accurate orbital-free DFT simulations of nanoscale systems out of equilibrium. Additionally, the proposed path to formulate nonadiabatic Pauli kernels presents several avenues for further improvements which can be exploited in future work to improve the results.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Automated Fiber Placement Manufactured Composites for Science Applications

Science instruments with large collecting areas that maintain dimensional stability, such as James Webb Space Telescope and Wide Field Space Telescope, help achieve next generation science advancements. Composite materials often used for science applications include high modulus fibers in cyanate ester matrices to result in dimensionally stable structures with low contamination. Hand lay-up fabrication is the most common approach for science instrument structures. Automated Fiber Placement (AFP) using intermediate modulus fibers is commonplace in aircraft production reducing manufacturing time and increasing quality and consistency. AFP manufacturing for future large science instruments can similarly reduce costs and increase reliability. However, high modulus fibers are more prone to damage than intermediate modulus fibers. This study investigates the manufacturing viability of M55J/RS3C (Tencate) slit tape material using AFP processing. Tencate provides slit tape materials. NASA Langley Research Center (LaRC) manufactured hand layup and AFP lay-up laminates under room temperature for initial trials, Marshall Space Flight Center (MSFC) manufactured AFP laminates under room temperature and elevated temperature conditions to evaluate processing affects. Goddard Space Flight Center (GSFC) tests and evaluates tension and Coefficient of Thermal Expansion (CTE) properties by hand lay-up and AFP slit tape automated manufacturing for large science applications. These results show processing material warm reduces process induced fiber fracture; leading to stiffness and CTE properties consistent with hand lay-up, while observing a slight degradation in tensile strength.

Segal, Kenneth N.↗

Impacts of Solar Land Availability on the Evolution of the U.S. Power System

Long-term planning scenarios of the United States electricity system have not identified solar resource availability to be a limiting factor in how much solar capacity might be deployed. However, there are some smaller regions where siting challenges indicate solar deployment could be limited by solar resource availability. In this work, we use geospatial modeling tools to develop a restrictive siting scenario that significantly reduces the amount and location of utility-scale solar resources. We use that restrictive siting regime, along with other previously defined siting scenarios, to examine how solar resource availability impacts the buildout of the electricity system using business-as-usual and decarbonization futures in a national-scale capacity expansion model. The restrictive siting scenario uses observed siting pressures to exclude many types of land on which development is allowed today and results in a greater than 90% reduction in solar resource potential-to approximately 3000 GW. Even with this drastic reduction, utility-scale solar capacity grows by more than 3 times through 2050 in the business-as-usual scenarios and by more than 6 times in the decarbonization scenarios, though less solar is deployed in scenarios with lower available solar resource. We quantify how system costs and generation mixes change as solar resource availability changes.

14 SOLAR ENERGY↗

Quantifying the impact of precision errors on quantum approximate optimization algorithms

The quantum approximate optimization algorithm (QAOA) is a hybrid quantum-classical algorithm that seeks to achieve approximate solutions to optimization problems by iteratively alternating between intervals of controlled quantum evolution. Here, we examine the effect of analog precision errors on QAOA performance from the perspective of both algorithmic training and performance guarantees. Leveraging cumulant expansions, we recast the faulty QAOA as a control problem in which precision errors are expressed as multiplicative control noise and derive bounds on the performance of QAOA. We show using both analytical techniques and numerical simulations that fixed precision implementations of QAOA circuits are subject to an exponential degradation in performance dependent upon the number of optimal QAOA layers and magnitude of the precision error. Despite this significant reduction, we show that it is possible to mitigate precision errors in QAOA via digitization of the variational parameters at the cost of increasing circuit depth.

quantum algorithms↗

How Today's Hydropower Impacts Tomorrow's Grid: Counterfactual Scenarios Showing Grid Impacts if Hydropower Goes Away

Amidst ongoing discussions about hydropower removals, retirements, and reduced availability due to drought and other environmental considerations, it is important to understand the long-term effects of reduced hydropower resources on the U.S. electric grid. This analysis uses the Regional Energy Deployment System (ReEDS™) grid planning model to compare several representative scenarios of retiring hydropower and pumped storage hydropower (PSH) capacity over time and explore the overall implications on the U.S. grid from present day through 2050. Reduced hydropower capacity and generation is replaced by a mix of both fossil and non-fossil resources, including natural gas, wind, solar, and battery technologies. Additional natural gas usage leads to an increase in cumulative national electric sector carbon dioxide and criteria pollutant operating emissions of less than 1% in many scenarios but up to 4-5.3% in some cases. Total electric sector costs also increase by <1% in many scenarios but up to 3.6% in the most extreme scenarios where nearly all the hydropower and PSH fleet retires, equating to $\$$340 billion in undiscounted costs. National results indicate that absent additional interventions, retiring hydropower and PSH capacity could increase electric sector emissions and direct capital and operating costs. However, more focused analysis is required to evaluate specific asset-level, local, and regional implications, and a broader scope is necessary to weigh these electric sector impacts alongside economic, ecological, water management, and other cross-sectoral effects that could be either negative or positive.

14 SOLAR ENERGY↗

Renewable Energy and Efficiency Technologies in Scenarios of U.S. Decarbonization in Two Types of Models: Comparison of GCAM Modeling and Sector-Specific Modeling

Energy system projections from analytic models inform actions ranging from short-term and local decisions, such as technology and infrastructure deployment, to global and long-term negotiations and targets. Computational limits require the designers of these models to trade off between coverage and resolution. Some models, such as the Global Change Analysis Model (GCAM), represent all energy sources and uses but at a relatively coarse level of resolution. GCAM balances global supply and demand of all energy carriers by endogenously projecting prices for energy sources and costs of greenhouse gas mitigation while capturing interlinkages between the energy system, water, agriculture and land use, the economy, and the climate. This global model was used to frame the Long-Term Strategy released by the White House in 2021 and has been used to inform national and global economy-wide decarbonization discussions and strategy development for decades. Other models instead focus on a portion of the energy sector with greater detail and resolution. The Regional Energy Deployment System (ReEDS) electricity-sector model, for example, projects capacity expansion with an emphasis on integration of variable renewable energy into the grid of the future. The Transportation Energy and Mobility Pathway Options (TEMPO) transportation-sector model enables analysis of household choices in adoption, charging, and use of electric vehicles. The Scout buildings-sector model supports detailed consideration of the policies and markets that can accelerate the adoption of energy conservation measures in buildings. Such sector-specific models are instrumental in informing technology research, sectoral planning strategies, and sector-specific aspects of greenhouse gas (GHG) mitigation strategies in the United States. These global and sector-specific modeling approaches can complement each other. The global approach ensures consistent, endogenous energy pricing and resource allocation, which can substantially diverge from current conditions in transformative scenarios, while the sector-specific approach facilitates representation of granular details across spatial, temporal, technological, and market dimensions that enable exploration of particular interactions and trade-offs. This report presents the results of recent work to explore the differences and tradeoffs between these approaches by comparing GCAM with the sector-specific ReEDS, TEMPO, and Scout models. The report compares both model structures and results, and discusses their potential relevance and applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA Space Missions to Asteroids: Protecting the Earth from NEO Impacts

There is now a general recognition of the hazard of impacts on Earth by comets and asteroids, but there is yet no consensus concerning international actions that should be taken to protect the planet from such impacts. An essential step in the analysis of the situation involves estimating the relative hazard posed by comets and asteroids of different sizes and orbits. All recent studies agree that the larger impacts pose the greater danger, and that our primary concern from the perspective of total risk should be on impacts that are large enough to cause global ecological catastrophe. These global catastrophes are also of special interest, since they (alone among natural disasters) have the potential to destroy civilization. Studies of the sensitivity of the Earth's environment suggest that the energy threshold energy for causing a global catastrophe is at about 1 million megatons, corresponding to impactor diameters of 1.5 to 2 km. This information leads naturally to a strategy of concentrating on the larger NEOs, say those 1 km or more in diameter. This is the rationale for the Spaceguard Survey, which must be the highest priority in mitigation efforts. The second question concerns the value of developing standing defensive systems that could deflect or destroy an incoming NEO. In the case of the asteroids larger than 1 km in diameter, no such system is needed, since there will be ample time (at least several decades) between the discovery of the threatening object by Spaceguard and the requirement to take action against it. In the case of objects smaller than 1 km diameter, development of defensive systems is not cost-effective; there are many greater dangers to persons and property that are much more urgent. Only in the case of large long-period comets is there a rationale for standing defense systems. The question is also raised whether the risks inherent in developing and maintaining a defense system might be greater than the impact risks it is intended to guard against. These and related issues are the focus of much current international debate on defense of the planet against NEO impacts. Meanwhile, the most critical issue remains the expansion of the telescopic search for NEOs.

Morrison, David↗

LLNS Request for Permanent Variance from 10 CFR 851 for Construction

Lawrence Livermore National Security, LLC (LLNS) requests variance from 10 CFR 851 (the Rule) for construction work at Lawrence Livermore National Laboratory (LLNL). The request is based upon successful application of similar variances granted to LLNS in continued support of the National Nuclear Security Administration (NNSA) initiative to streamline the delivery of line-item construction projects under $50 million. This request is aligned with the approved NA 50 safety approach. Experience gained in the construction of the new LLNL Emergency Operations Center (EOC) under the variance granted in June 2020 and construction preparations to date on the Digital Infrastructure Capabilities Expansion (DICE) under the variance granted April 2022 is very encouraging. There are strong indicators that a benefit has been realized by both the subcontractors executing the work and the Laboratory. The variance has permitted local/regional construction businesses contracted to Management & Operation Contractor operated facilities and lower tier subcontractors to bid, operate, execute, and comply with safety and health standards they utilize in their business outside of the Department of Energy (DOE) Complex. While compliance to standards that are as safe and healthful as those in 10 CFR 851: confusion, additional cost, and inefficiencies associated with the burden of compliance to an unfamiliar regulatory spectrum has been avoided. Safety and health performance on the construction project including the number of inspection and surveillance issues is comparable to other subcontractors and projects at LLNL executed under 10 CFR 851. This variance application was prepared according to the requirements in 10 CFR 851, Subpart D – Variances, § 851.31 Variance Process. This request is limited to subcontractor executed construction at LLNL.

42 ENGINEERING↗

Performance of Low Dissipative High Order Shock-Capturing Schemes for Shock-Turbulence Interactions

Accurate and efficient direct numerical simulation of turbulence in the presence of shock waves represents a significant challenge for numerical methods. The objective of this paper is to evaluate the performance of high order compact and non-compact central spatial differencing employing total variation diminishing (TVD) shock-capturing dissipations as characteristic based filters for two model problems combining shock wave and shear layer phenomena. A vortex pairing model evaluates the ability of the schemes to cope with shear layer instability and eddy shock waves, while a shock wave impingement on a spatially-evolving mixing layer model studies the accuracy of computation of vortices passing through a sequence of shock and expansion waves. A drastic increase in accuracy is observed if a suitable artificial compression formulation is applied to the TVD dissipations. With this modification to the filter step the fourth-order non-compact scheme shows improved results in comparison to second-order methods, while retaining the good shock resolution of the basic TVD scheme. For this characteristic based filter approach, however, the benefits of compact schemes or schemes with higher than fourth order are not sufficient to justify the higher complexity near the boundary and/or the additional computational cost.

Sandham, N. D.↗

Performance of Low Dissipative High Order Shock-Capturing Schemes for Shock-Turbulence Interactions

Abstract Accurate and efficient direct numerical simulation of turbulence in the presence of shock waves represents a significant challenge for numerical methods. The objective of this paper is to evaluate the performance of high order compact and non-compact central spatial differencing employing total variation diminishing (TVD) shock-capturing dissipations as characteristic based filters for two model problems combining shock wave and shear layer phenomena. A vortex pairing model evaluates the ability of the schemes to cope with shear layer instability and eddy shock waves, while a shock wave impingement on a spatially-evolving mixing layer model studies the accuracy of computation of vortices passing through a sequence of shock and expansion waves. A drastic increase in accuracy is observed if a suitable artificial compression formulation is applied to the TVD dissipations. With this modification to the filter step the fourth-order non-compact scheme shows improved results in comparison to second-order methods, while retaining the good shock resolution of the basic TVD scheme. For this characteristic based filter approach, however, the benefits of compact schemes or schemes with higher than fourth order are not sufficient to justify the higher complexity near the boundary and/or the additional computational cost.

Sandham, N. D.↗

Quantum Adiabatic Algorithms and Large Spin Tunnelling

We provide a theoretical study of the quantum adiabatic evolution algorithm with different evolution paths proposed in this paper. The algorithm is applied to a random binary optimization problem (a version of the 3-Satisfiability problem) where the n-bit cost function is symmetric with respect to the permutation of individual bits. The evolution paths are produced, using the generic control Hamiltonians H (r) that preserve the bit symmetry of the underlying optimization problem. In the case where the ground state of H(0) coincides with the totally-symmetric state of an n-qubit system the algorithm dynamics is completely described in terms of the motion of a spin-n/2. We show that different control Hamiltonians can be parameterized by a set of independent parameters that are expansion coefficients of H (r) in a certain universal set of operators. Only one of these operators can be responsible for avoiding the tunnelling in the spin-n/2 system during the quantum adiabatic algorithm. We show that it is possible to select a coefficient for this operator that guarantees a polynomial complexity of the algorithm for all problem instances. We show that a successful evolution path of the algorithm always corresponds to the trajectory of a classical spin-n/2 and provide a complete characterization of such paths.

Boulatov, A.↗

Scrambling and quantum chaos indicators from long-time properties of operator distributions

Scrambling is a key concept in the analysis of nonequilibrium properties of quantum many-body systems. Most studies focus on its characterization via out-of-time-ordered correlation (OTOC) functions, particularly through the early-time decay of the OTOC. However, scrambling is a complex process which involves operator spreading and operator entanglement, and a full characterization requires one to access more refined information on the operator dynamics at several timescales. In this work we analyze operator scrambling by expanding the target operator in a complete basis and studying the structure of the expansion coefficients treated as a coarse-grained probability distribution in the space of operators. Here we study different features of this distribution, such as its mean, variance, and participation ratio, for the Ising model with longitudinal and transverse fields, kicked collective spin models, and random circuit models. We show that the long-time properties of the operator distribution display common features across these cases and discuss how these properties can be used as a proxy for the onset of quantum chaos. Finally, we discuss the connection with OTOCs and analyze the cost of probing the operator distribution experimentally using these correlation functions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗