Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Competition”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Evaluating the regional risks to food availability and access from land-based climate policies in an Integrated Assessment Model

Mitigating greenhouse gas (GHG) emissions is necessary to reduce the overall negative climate change impacts on crop yields and agricultural production. However, certain mitigation measures may generate unintended consequences to food availability and food access due to both land use competition and economic burden of mitigation. Integrated assessment models (IAM) are generally used to evaluate these policies; however, currently these models may not capture the importance of income and food prices for hunger and overall economic wellbeing. Here, we implement a measure of food security that captures the nutritional and economic aspects as the total expenditures on staple foods divided by income and weighted by total caloric consumption in an IAM, the Global Change Analysis Model (GCAM4.0). We then project consumer prices and our measure of food security along the Shared Socioeconomic Pathways (SSPs). Sustained economic growth underpins increases in caloric consumption and lowering expenditures on staple foods. Strict conservation policies affect food accessibility in a larger number of developing countries, whereas the negative effects of pricing terrestrial emissions is more concentrated on the poor in Sub-Saharan Africa, by substantially replacing their cropland with forests and affecting the production of key staples.

Cui, Ryna↗
DOE OSTI2024

An Empirical Quantile Estimation Approach for Chance-Constrained Nonlinear Optimization Problems

We investigate an empirical quantile estimation approach to solve chance-constrained nonlinear optimization problems. Our approach is based on the reformulation of the chance constraint as an equivalent quantile constraint to provide stronger signals on the gradient. In this approach, the value of the quantile function is estimated empirically from samples drawn from the random parameters, and the gradient of the quantile function is estimated via a finite-difference approximation on top of the quantile-function-value estimation. We establish a convergence theory of this approach within the framework of an augmented Lagrangian method for solving general nonlinear constrained optimization problems. The foundation of the convergence analysis is a concentration property of the empirical quantile process, and the analysis is divided based on whether or not the quantile function is differentiable. In contrast to the sampling-and-smoothing approach used in the literature, the method developed in this paper does not involve any smoothing function and hence the quantile-function gradient approximation is easier to implement and there are less accuracy-control parameters to tune. Furthermore, we demonstrate the effectiveness of this approach and compare it with a smoothing method for the quantile-gradient estimation. Numerical investigation shows that the two approaches are competitive for certain problem instances.

Applied Probability↗
DOE OSTI2021

Impacts of The Wetland Sedge Carex aquatilis on Microbial Community and Methane Metabolisms

Microbial activity in the soil of wetlands is responsible for the emission of more methane to the atmosphere than all other natural sources combined. This microbial activity is heavily impacted by plant roots, which influence the microbial community by exuding organic compounds and by leaking oxygen into an otherwise anoxic environment. This study compared the microbial communities of planted and unplanted wetland soil from an Alaskan bog to elucidate how plant growth influences populations and metabolisms of methanogens and methanotrophs. A common boreal wetland sedge, Carex aquatilis, was grown in the laboratory and DNA samples were sequenced from the rhizosphere, unplanted bulk soil, and a simulated rhizosphere with oxygen input but no organic carbon. The abundance of both methanogens and methanotrophs were positively correlated with methane emissions. Among the methanotrophs, both aerobic and anaerobic methane oxidizing microbes were more common in the rhizosphere of mature plants than in unplanted soil, while facultative methanotrophs capable of utilizing either methane or other molecules became relatively less common. Furthermore, these trends indicate that the roots in this experiment created an environment which favored highly specialized microbial metabolisms over generalist approaches. One aspect of this specialized microbiome is the presence of both aerobic and anaerobic metabolisms, which indicates that oxygen is present but is a limiting resource controlling competition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Performance evaluations of signed and unsigned noisy approximate quantum Fourier arithmetic

The Quantum Fourier Transform (QFT) grants competitive advantages, especially in resource usage and circuit approximation, for performing arithmetic operations on quantum computers, and offers a potential route toward a numerical quantum-computational paradigm. In this paper, we utilize efficient techniques to implement QFT-based integer addition and multiplications. These operations are fundamental to various quantum applications including Shor’s algorithm, weighted-sum optimization problems in data processing and machine learning, and quantum algorithms requiring inner products. We carry out performance evaluations of these implementations based on IBM’s superconducting-qubit architecture using different compatible noise models. We isolate the sensitivity of the component quantum circuits on both one-/two-qubit gate error rates, and the number of the arithmetic operands’ superposed integer states. We analyze performance and identify the most effective approximation depths for unsigned quantum addition and quantum multiplication within the given context. We then perform a similar analysis of signed addition and compare to the unsigned results. We observe significant dependency of the optimal approximation depth on the degree of machine noise and the number of superposed states in certain performance regimes. Finally, we elaborate on the algorithmic challenges—relevant to signed, unsigned, modular and non-modular versions—that could also be applied to current implementations of QFT-based subtraction, division, exponentiation, and their potential tensor extensions. Here, we analyze the performance trends in our results and speculate on possible future developments within this computational paradigm.

Computational models↗
DOE OSTI2023

Direct Estimation of Parameters in ODE Models Using WENDy: Weak-Form Estimation of Nonlinear Dynamics

Abstract We introduce the Weak-form Estimation of Nonlinear Dynamics (WENDy) method for estimating model parameters for non-linear systems of ODEs. Without relying on any numerical differential equation solvers, WENDy computes accurate estimates and is robust to large (biologically relevant) levels of measurement noise. For low dimensional systems with modest amounts of data, WENDy is competitive with conventional forward solver-based nonlinear least squares methods in terms of speed and accuracy. For both higher dimensional systems and stiff systems, WENDy is typically both faster (often by orders of magnitude) and more accurate than forward solver-based approaches. The core mathematical idea involves an efficient conversion of the strong form representation of a model to its weak form, and then solving a regression problem to perform parameter inference. The core statistical idea rests on the Errors-In-Variables framework, which necessitates the use of the iteratively reweighted least squares algorithm. Further improvements are obtained by using orthonormal test functions, created from a set of $$C^{\infty }$$ C ∞ bump functions of varying support sizes.We demonstrate the high robustness and computational efficiency by applying WENDy to estimate parameters in some common models from population biology, neuroscience, and biochemistry, including logistic growth, Lotka-Volterra, FitzHugh-Nagumo, Hindmarsh-Rose, and a Protein Transduction Benchmark model. Software and code for reproducing the examples is available at https://github.com/MathBioCU/WENDy .

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Quantifying Equiaxed vs Epitaxial Solidification in Laser Melting of CMSX-4 Single Crystal Superalloy

The competition between epitaxial vs. equiaxed solidification has been investigated in CMSX-4 single crystal superalloy during laser melting as practiced in additive manufacturing. Single-track laser scans were performed on a powder-free surface of directionally solidified CMSX-4 alloy with several combinations of laser power and scanning velocity. Electron backscattered diffraction (EBSD) mapping facilitated identification of new orientations, i.e., “stray grains” that nucleated within the fusion zone along with their area fraction and spatial distribution. Using high-fidelity computational fluid dynamics simulations, both the temperature and fluid velocity fields within the melt pool were estimated. This information was combined with a nucleation model to determine locations where nucleation has the highest probability to occur in melt pools. In conformance with general experience in metals additive manufacturing, the as-solidified microstructure of the laser-melted tracks is dominated by epitaxial grain growth; nevertheless, stray grains were evident in elongated melt pools. It was found that, though a higher laser scanning velocity and lower power are generally helpful in the reduction of stray grains, the combination of a stable keyhole and minimal fluid velocity further mitigates stray grains in laser single tracks.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A Limit to Accelerated Free-Sintering: Nano-Phase Separation Interferes With Organic Debinding

Nano-phase separating Ni–12 at. pct Ag powders are processed via high-energy ball milling and brought into a supersaturated state with a reduction of the grain size to the nanocrystalline scale, a combination that is designed to encourage rapid densification by phase separation upon heating. This unstable powder is then characterized by dilatometry, in-situ x-ray diffraction, thermogravimetry and microstructure analysis for sintering cycles up to 940 °C. However, these powder compacts exhibit excessive pore evolution and significant macroscopic swelling caused by removal of the organic process additives. This competition of organic removal with densification is known in nanocrystalline metals, but the present study adds an additional dimension of phase separation, which shifts the dominant swelling mechanism as the formation of the second phase traps the volatilizing organics and hinders the debinding process. The creep swelling and overall loss in relative density is then dominated by the creep deformation of the second Ag phase. The interference between organic removal and low-temperature onset of consolidation represents a new challenge to efforts aimed at rapid free sintering and should guide the design of rapidly sintering alloys; specifically, the present work emphasizes the need to select alloys that have their sintering-accelerating phase separation temperature above the range where gases are evolved.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A General Model for the Ductility of Intermetallics Applied to Fe-Co Alloys

The mechanical properties, specifically ductility, of high performing soft magnets such as Fe-Co alloys are a limiting factor to their broader use in a number of systems. The understanding of the mechanical robustness in these materials is currently insufficient to be able to support the growing interest in applications such as magnetic shielding or electric motors. Fe-Co alloys provide the highest commercially available magnetic saturation and high magnetic permeability but have very poor ductility. The addition of vanadium to these alloys has allowed for significant commercialization and some ductility improvements, but the fundamental reasons for the observed improvements are not well understood. In most published work on mechanical properties in these alloys, the precise chemistry of the alloys investigated, often a critical aspect of intermetallics, is not reported or controlled and thermal history is unclear. This work creates a ductility model that is sensitive to changes in chemistry and can predict relative strain to failure as well as brittle fracture mode for intermetallics and is applied to Fe-Co alloys. Through the application of density functional theory (DFT), this model identifies defect stabilities, anti-phase boundary (APB) energies, the energy necessary to cross-slip, and cleavage energies and combines them through energetic competition to determine a relative failure strain. The model correctly predicts ductility improvements with the addition of vanadium as well as the transition from intergranular to transgranular cleavage, though more precise experiments are necessary to appropriately validate the various improvements observed.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Iron Oxide Reduction Rate Affects Iron Product Morphology

Magnetite concentrates from different parts of the Mesabi Range, exhibiting varying tendencies to encapsulate, were reduced using thermogravimetric analysis (TGA) and a high-temperature confocal scanning laser microscope (CSLM). Gas-phase mass-transfer conditions were intentionally varied by employing two reactors with different geometries: the TGA produced significantly slower reduction, whereas the CSLM setup yielded reduction rates up to 20 times faster under mass-transfer-controlled conditions. A preliminary mechanism is proposed to explain the transition from a porous iron product to a dense encapsulating layer. Encapsulation is interpreted as the outcome of competition between pore creation, driven by the reduction rate, and pore elimination, driven by surface diffusion. When pore formation is insufficient to counteract pore coarsening, a dense iron layer develops and restricts further reduction.

encapsulation↗
DOE OSTI2023

Synchrotron x-Ray Study of Heterostructured Materials: A Review

Heterostructured materials (HSMs) have shown great potential for breaking the strength-ductility tradeoff. HSMs consist of heterogeneous zones that may have different sizes, shapes, compositions, structures, etc. Interactions and competitions among them often lead to unprecedented properties. However, due to the complex structures in a broad range of length scales, it is challenging to unravel deformation physics and strengthening mechanisms underlying extraordinary mechanical properties. Synchrotron x-rays provide powerful techniques and indispensable tools for investigating HSMs at various length scales. Here, we will present in situ high-energy x-ray diffraction and Laue x-ray microdiffraction techniques and their application in studying the HSMs. In this study, the principles of these techniques will be briefly introduced. We will focus on their application in studying stress partitioning and plastic accommodation during tensile deformation, thermo-driven and/or stress-driven phase transformations and various deformation microstructures like geometrically necessary dislocations and local stress/strain distributions, etc., in HSMs. Some important findings will be summarized. Challenging issues remain in studying HSMs and will be discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Friction Extrusion: Solid-State Metal Synthesis and Recycling in Sustainable Manufacturing

Friction extrusion (FE) is a novel solid-state process for synthesis and recycling of metals and alloys. The novelty of FE is that it utilizes the frictional heating and extensive plastic deformation intrinsic in the process to stir, mechanically alloy, consolidate, and convert powders, chips, and other recyclable feedstock metals into a usable product form of highly engineered materials. FE represents a potentially transformational sustainable manufacturing technology. Being a solid-state process, it eliminates the energy-intensive melting and solidification steps, which are necessary in the conventional metal recycle and synthesis processes. Therefore, FE is a highly energy-efficient, practically zero-emission, and economically competitive process. Here, in this work, the concept and configuration of FE are introduced, the energy-saving advantage of FE is analyzed, the feasibility of FE is demonstrated with synthesizing Al alloys, and the results of some metallographic and mechanical properties studies are presented. A prognosis of the friction extrusion technology is outlined.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Grain Structure Evolution in Fe-6Si During Directed Energy Deposition

The purpose of this study is to explore the effect of additive manufacturing (AM) process variables on the grain structure of Fe-6Si, a soft-magnetic alloy used in electrical machine and grid applications. Samples were fabricated with laser engineered net shaping (LENS) with varying inter-pass timing and numbers of unidirectional passes. Here the results show that the grain structure was affected by both solidification and solid-state grain growth mechanisms. A model of the LENS process suggests that, although shorter inter-pass times encourage greater nucleation of new grains and therefore grain refinement during solidification, these conditions also help maintain high solid-state temperatures that allow for grain boundary motion to keep pace with the build rate. Grains formed under these conditions may span multiple layers, and the high-temperature gradient promotes directional growth. This new understanding of these microstructure evolution mechanisms will aid in using process conditions to control the competition between solidification and solid-state grain growth to create grain structures that may not be possible with conventional processing.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Implementing a unified solver for nonlinearly constrained optimization

SQP and interior-point methods (also referred to as Lagrange-Newton methods) typically share key algorithmic components, such as strategies for computing descent directions and mechanisms that promote global convergence. Building on this insight, we introduce a unifying framework with eight building blocks that abstracts the workflows of Lagrange-Newton methods. We then present Uno, a modular C++ solver that implements our unifying framework and allows the automatic combination of a wide range of strategies with no programming effort from the user. Uno is meant to (1) organize mathematical optimization strategies into a coherent hierarchy; (2) offer a wide range of efficient and robust methods that can be compared for a given instance; (3) enable researchers to experiment with novel optimization strategies; and (4) reduce the cost of development and maintenance of multiple optimization solvers. Uno’s software design allows user to compose new customized solvers for emerging optimization areas such as robust optimization or optimization problems with complementarity constraints, while building on reliable nonlinear optimization techniques. We demonstrate that Uno is highly competitive against state-of-the-art solvers filterSQP, IPOPT, SNOPT, MINOS, LANCELOT, LOQO, and CONOPT on a subset of 429 small problems from the CUTE collection. Uno is available as open-source software under the MIT license at https://github.com/cvanaret/Uno and via its C, Julia, Python, Fortran, and AMPL interfaces.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Predictive models enhance feedstock quality of corn stover via air classification

Feedstock heterogeneity is a fundamental obstacle to cost-competitive biobased products. Agricultural products like corn stover have anatomical components that vary in their chemical composition, mechanical properties, structure, and response to chemical and biological treatments. A technique that can enrich streams in select anatomical fractions would allow a tailored deconstruction approach to increase overall process efficiency. Air classification can be leveraged for such refining, however, fundamental characterization and understanding of the particle properties that underly the physics of air classification are only modestly documented. Here, we determine fundamental particle properties including mass-to-area ratio, drag coefficient, and partition velocity that describe how anatomical tissues of corn stover behave during air classification. In this work, mass-to-area ratios of anatomical tissues vary by nearly two orders of magnitude from 2.3 mg/mm 2 for cob to 0.04 mg/mm 2 for leaf. Drag coefficients of longer, fibrous materials (i.e., rind, husk, and sheath) are shown to correlate with particle area (p-value < 0.001) whereas granular tissues (i.e., cob, pith, and leaf) correlate better with mass-to-area ratio (p-values < 0.001). When compared to experimental observations, a simulated two-stage air classification and size reduction scenario predicts the overall partitioning of anatomical tissues within 15% for pith, husk, rind, and cob tissues. The model predicts an air-classified fraction preferentially enriched in cob (purity = 20%), rind (purity = 74%), and pith (purity = 4.5%) with a mass yield of 47%. Empirical relations for these properties can be used to predict the partitioning of corn stover during air classification based on anatomical type and size.

09 BIOMASS FUELS↗
DOE OSTI2023

Mechanistic Insights into the Catalytic Condensation of Methyl Ketones on MgO Surfaces

Ketone coupling via aldol condensation is one of the promising routes to produce cyclic and value-added precursors for renewable hydrocarbon biofuels. A first-principles-based microkinetic modeling is performed to evaluate the surface-mediated reaction mechanisms and the role of water molecules in the observed activities for 2-pentanone and 3-pentanone aldol condensation on dehydroxylated MgO(111) surface and hydroxylated terminated surface[OH-MgO(111)]. Here, we have identified the enhancement of the surface OH group to MgO(111) surface catalytic activity by destabilizing the binding strength of reaction intermediates and reducing the energy barriers of rate-determining steps(proton transfer and dehydration steps). The 2-pentanone has one elementary step less in the complete reaction mechanism of aldol condensation and preferable energy barrier for proton transfer and dehydration steps, revealing 2-pentanone as terminal ketone is more reactive than 3-pentanone as central ketone. The water molecules dominated the OH-MgO( 111) surface after further addition of water, leading to the reduction of turnover frequency of the aldol condensation dimer product as the loss of aldol condensation reaction intermediates in competitive adsorption with water molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Change Agent: Energy Storage as a Driver of Regulatory Evolution

Purpose of Review Dividing the electric grid into the functions of generation, transmission, anddistribution enabled the drawing of jurisdictional lines and the application of the U.S.Constitution’s federalist system to energy regulation. Energy storage technologies,which can be placed throughout the grid to increase flexibility, can provide serviceacross all three of those functions. But the jurisdictional boundaries that have beendrawn around those functions have created barriers that restrict energy storagetechnologies from achieving their full potential. This review analyzes regulatory changes made to reduce barriers to storage deployment and their broader impacts on energy regulation in the U.S. Recent Findings Major energy regulations promulgated at the state and federal levels have generally focused on liberalizing the U.S. electric system through deregulation and increased competition. Paradoxically, however, these efforts have erected strict regulatory barriers that prevent energy storage technologies from providing service across multiple functions. A new wave of regulations in recent years has endeavored to reduce and remove those barriers. Summary Energy regulations adopted in recent years to reduce barriers to energy storage functionality in recent years have had deep and far-reaching impacts on U.S. electric regulation. These impacts go beyond storage and affect all energy technologies. This paper traces the development of energy regulation in U.S., the functional barriers that they created that impede energy storage functionality, recent efforts to remove those barriers, and the broader effects of those efforts. It concludes with a brief discussion of remaining barriers that prevent energy storage from reaching their full potential on the U.S. electric grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Combining shallow-water and analytical wake models for tidal array micro-siting

For tidal-stream energy to become a competitive renewable energy source, clustering multiple turbines into arrays is paramount. Array optimisation is thus critical for achieving maximum power performance and reducing cost of energy. However, ascertaining an optimal array layout is a complex problem, subject to specific site hydrodynamics and multiple inter-disciplinary constraints. In this work, we present a novel optimisation approach that combines an analytical-based wake model, FLORIS, with an ocean model, Thetis. The approach is demonstrated through applications of increasing complexity. By utilising the method of analytical wake superposition, the addition or alteration of turbine position does not require re-calculation of the entire flow field, thus allowing the use of simple heuristic techniques to perform optimisation at a fraction of the computational cost of more sophisticated methods. Using a custom condition-based placement algorithm, this methodology is applied to the Pentland Firth for arrays with turbines of 3.05 m/s rated speed, demonstrating practical implications whilst considering the temporal variability of the tide. For a 24-turbine array case, micro-siting using this technique delivered an array 15.8% more productive on average than a staggered layout, despite flow speeds regularly exceeding the rated value. Performance was evaluated through assessment of the optimised layout within the ocean model that treats turbines through a discrete turbine representation. Used iteratively, this methodology could deliver improved array configurations in a manner that accounts for local hydrodynamic effects.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Technoeconomic and life cycle energy analysis of carbon fiber manufactured from coal via a novel solvent extraction process

Coal is a versatile energy resource and was a driver of the industrial revolution that transformed the economies of Europe and North America and the trajectory of civilization. In this work, a technoeconomic analysis was performed for a coal-to-carbon-fiber manufacture process developed at the University of Kentucky’s Center for Applied Energy Research. According to this process, coal, with decant oil as the solvent, was converted to mesophase pitch via solvent extraction, and the mesophase pitch was subsequently converted to carbon fiber. The total cost to produce carbon fibers from coal and decant oil via the solvent extraction process was estimated to be $\$$11.50/kg for 50,000-tow pitch carbon fiber with a production volume of 3750 MT/year. The estimated carbon fiber cost was significantly lower than the current commercially available PAN-based carbon fiber price ($\$$20–$\$$30/kg). With decant oil recycling rates of 50% and 70% in the solvent extraction process, the manufacturing cost of carbon fiber was estimated to be $\$$9.90/kg and $\$$9.50/kg of carbon fiber, respectively. A cradle-to-gate energy assessment revealed that carbon fiber derived from coal exhibited an embodied energy of 510 MJ/kg, significantly lower than that of conventionally produced carbon fiber from PAN. This notable difference is primarily attributed to the substantially higher conversion rate of coal-based mesophase pitch fibers into carbon fiber, surpassing PAN fibers by 1.6 times. These findings indicate that using coal for carbon fiber production through solvent extraction methods could offer a more energy-efficient and cost-competitive alternative to the traditional PAN based approach.

01 COAL, LIGNITE, AND PEAT↗