Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “REDUCTION”

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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Enhancing Oxygen Reduction Activity of Pt-based Electrocatalysts: From Theoretical Mechanisms to Practical Methods

Pt-based electrocatalysts are considered as one of the most promising choices to facilitate the oxygen reduction reaction (ORR), and the key factor enabling their success is to reduce the required amount of platinum. Herein, we focus on illuminating both the theoretical mechanisms which enable enhanced and sustained ORR activity and the practical methods to achieve them in catalysts. The various multi-step pathways of ORR are firstly reviewed and the rate-determining steps based on the reaction intermediates and their binding energies are analyzed. We then explain the critical aspects of Pt-based electrocatalysts to tune oxygen reduction properties from the viewpoints of active sites exposure and altering the surface electronic structure, and further summarize representative research progress towards practically achieving these activity enhancements with a focus on platinum size reduction, shape control and core Pt elimination methods. Finally, we outline the remaining challenges and provide our perspectives with regard to further enhancing their activities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Activation of Transition Metal (Fe, Co and Ni)-Oxide Nanoclusters by Nitrogen Defects in Carbon Nanotube for Selective CO 2 Reduction Reaction

The electrochemical carbon dioxide reduction reaction (CO2RR), which can produce value-added chemical feedstocks, is a proton-coupled-electron process with sluggish kinetics. Thus, highly efficient, cheap catalysts are urgently required. Transition metal oxides such as CoO x , FeO x , and NiO x are low-cost, low toxicity, and abundant materials for a wide range of electrochemical reactions, but are almost inert for CO 2 RR. Here, we report for the first time that nitrogen doped carbon nanotubes (N-CNT) have a surprising activation effect on the activity and selectivity of transition metal-oxide (MO x where M = Fe, Ni, and Co) nanoclusters for CO 2 RR. MO x supported on N-CNT, MOx/N-CNT, achieves a CO yield of 2.6–2.8 mmol cm -2 min -1 at an overpotential of -0.55V, which is two orders of magnitude higher than MO x supported on acid treated CNTs (MOx/O-CNT) and four times higher than pristine N-CNT. The faraday efficiency for electrochemical CO 2 -to-CO conversion is as high as 90.3% at overpotential of 0.44V. Both in-situ XAS measurements and DFT calculations disclose that MO x nanoclusters can be hydrated in CO 2 saturated KHCO 3 , and the N defects of N-CNT effectively stabilize these metal hydroxyl species under carbon dioxide reduction reaction conditions, which can split the water molecules and provide local protons to inhibit the poisoning of active sites under carbon dioxide reduction reaction conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Kernel Manifolds: Nonlinear‐Augmentation Dimensionality Reduction Using Reproducing Kernel Hilbert Spaces

This paper generalizes recent advances on quadratic manifold (QM) dimensionality reduction by developing kernel methods-based nonlinear-augmentation dimensionality reduction. QMs, and more generally feature map-based nonlinear corrections, augment linear dimensionality reduction with a nonlinear correction term in the reconstruction map to overcome approximation accuracy limitations of purely linear approaches. While feature map-based approaches typically learn a least squares optimal polynomial correction term, we generalize this approach by learning an optimal nonlinear correction from a user-defined reproducing kernel Hilbert space. Our approach allows one to impose arbitrary nonlinear structure on the correction term, including polynomial structure, and includes feature map and radial basis function-based corrections as special cases. Furthermore, our method has relatively low training cost and has monotonically decreasing error as the latent space dimension increases. In conclusion, we compare our approach to proper orthogonal decomposition and several recent QM approaches on data from several example problems.

kernel methods↗
DOE OSTI2025

Neural Active Manifolds: Nonlinear Dimensionality Reduction for Uncertainty Quantification

We present a new approach for nonlinear dimensionality reduction, specifically designed for computationally expensive mathematical models. We leverage autoencoders to discover a one-dimensional neural active manifold (NeurAM) capturing the model output variability, through the aid of a simultaneously learnt surrogate model with inputs on this manifold. Our method only relies on model evaluations and does not require the knowledge of gradients. The proposed dimensionality reduction framework can then be applied to assist outer loop many-query tasks in scientific computing, like sensitivity analysis and multifidelity uncertainty propagation. In particular, we prove, both theoretically under idealized conditions, and numerically in challenging test cases, how NeurAM can be used to obtain multifidelity sampling estimators with reduced variance by sampling the models on the discovered low-dimensional and shared manifold among models. Several numerical examples illustrate the main features of the proposed dimensionality reduction strategy and highlight its advantages with respect to existing approaches in the literature.

Autoencoders↗
DOE OSTI2019

Mechanisms and Kinetics of Reduction of Solid NiO in CO/CO{sub 2} and CO/Ar Gas Mixtures

Experimental studies have been carried out on the reduction of dense nickel oxide in CO/CO{sub 2} and CO/Ar gas mixtures at temperatures between 873 K and 1273 K (600 °C and 1000 °C). Examination of the nickel product microstructures of partially reduced samples has been undertaken using high-resolution scanning electron microscopy. It has been shown that the reduction can result in the formation of a dense nickel layer at the sample surface, continuous gas pore growth in the NiO, or the discontinuous growth of the porous nickel product. The product morphologies formed, and the microstructures of the gas/metal oxide/metal interfaces, are functions of reaction temperature and gas conditions. The microstructural and kinetic evidence indicates direct links between the reduction rates, nickel product growth mechanisms, and product microstructures.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Closure of Internal Porosity in Continuous Casting Bloom During Heavy Reduction Process

To investigate the closure behavior of internal porosity (also referred to as internal void) in continuous casting bloom during heavy reduction (HR) and thus provide theoretical guidance for minimizing this kind of internal defect more effectively with HR, a three-dimensional (3D) mechanical model was developed based on the predicted temperature field by a 2D heat transfer model. With this 3D mechanical model, closure behaviors of internal porosity in continuous casting bloom during HR at and after the strand solidification end under different process conditions were numerically studied. It was found that the void axis length decreased significantly along the bloom thickness direction and increased slightly along the casting and bloom width directions after HR, and the influence of the initial void size on the void closure was not obvious. With a decrease of temperature difference between the bloom surface and center, HR efficiency for minimizing internal void decreased, while the required reduction force significantly increased. Compared with blooms with a uniform temperature distribution of 1100 °C, the void closure index after HR implemented at the strand solidification end was increased by ~ 25 pct. Compared with a conventional flat roll, the application of a convex roll during HR could contribute to minimizing the internal porosity more effectively and significantly enhance the reduction capacity of the withdrawal and straightening units. The void closure index of η{sub s} and η{sub v} (where η{sub s} and η{sub v} were defined based on the variation of the void aspect ratio and the void volume, respectively) was closely related to the equivalent strain (ε{sub eq}) and the hydrostatic integration parameter (Q), respectively, and two mathematical equations were derived to quantitatively describe the relationship of η{sub s} − ε{sub eq} and η{sub v} − Q.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Carbon flowers as electrocatalysts for the reduction of oxygen to hydrogen peroxide

Small-scale and decentralized production of H 2 O 2 via electrochemical reduction of oxygen is of great benefit, especially for sanitization, air and water purification, as well as for a variety of chemical processes. The development of low-cost and high-performance catalysts for this reaction remains a key challenge. Carbon-based materials have drawn substantial research efforts in recent years due to their advantageous properties, such as high chemical stability and high tunability in active sites and morphology. Deeper understanding of structure–activity relationships can guide the design of improved catalysts. We hypothesize that mass transport to active sites is of great importance, and herein we use carbon materials with unique flower-like superstructures to achieve high activity and selectivity for O 2 reduction to H 2 O 2 . The abundance of nitrogen active sites controlled by pyrolysis temperature resulted in high catalytic activity and selectivity for oxygen reduction reaction (ORR). The flower superstructure showed higher performance than the spherical nanoparticles due to greater accessibility to the active sites. Chemical activation improves the catalysts’ performances further, driving the production of H 2 O 2 to a record-setting rate of 816 mmol·g cat -1 ·h -1 using a bulk electrolysis setup. In conclusion, this work demonstrates the development of a highly active catalyst for the sustainable production of H 2 O 2 through rational design and synthetic control. The understanding from this work provides further insight into the design of future carbon-based electrocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

A New One-Pot Sequential Reduction-Deposition Method for the synthesis of Silica-supported NiPt and CuPt Bimetallic Catalysts

A one-pot redox deposition method is described to prepare silica-supported bimetallic NiPt and CuPt catalysts using differences in standard reduction potentials. The synthesis involved the initial reduction of non-noble metal ions (Ni 2+ and Cu 2+ ) by NaBH 4 , followed by reduction of Pt ions by these reduced metals. Alloy formation and phase purity were established by X-ray diffraction (XRD), bulk composition by X-ray fluorescence (XRF), and surface composition by X-ray photoelectron spectroscopy (XPS). Alloy formation was enhanced by increase in the amount of base metals available to reduce Pt, or through the use of excess NaBH 4 after redox deposition. The catalysts were evaluated for methane oxidation at 300-400 °C and atmospheric pressure. Reference samples prepared using the incipient wetness impregnation (IW) method had inferior performance and characteristics. The redox deposition method provides a simple and versatile protocol for the preparation of bimetallic alloys between noble metals and base metals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Sequentially prepared Mo-V-Based SCR catalyst for simultaneous Hg 0 oxidation and NO reduction

Molybdenum (Mo)-vanadium (V)-based selective catalytic reduction (SCR) catalyst synthesized by the sequential impregnation of Mo and W followed by V was investigated for simultaneous elemental mercury (Hg 0 ) oxidation and nitrogen oxide (NO) reduction in an existing SCR unit with respect to different TiO 2 phases, calcination temperatures, flue gas constituents, gas velocities, and reaction temperatures. Anatase phase TiO 2 and the calcination temperatures of 400 and 500 degrees C resulted in similar to 69% Hg 0 oxidation at 10 ppmv HCl and 350 degrees C. The high calcination temperature of 700 degrees C resulted in TiO 2 phase transformation from anatase to rutile and agglomeration. The modified SCR catalyst prepared with the impregnation sequence of Mo and W followed by V using anatase TiO 2 and calcination temperature 500 degrees C showed similar to 99% Hg 0 oxidation and 87% NO reduction conversions at an NH 3 /NO molar ratio of 0.9 under 350 degrees C and 5,000 hr -1 space velocity in typical sub-bituminous and lignite coal simulated flue gases. Finally, the effects of these parameters and conditions were further investigated using various characterization techniques including BET, TEM, XRD, NH 3 TPD and XAFS.

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

The role of transition metal formyl intermediates in the reduction of CO and CO 2

Transition-metal formyl (metalloformyl) complexes occupy a central position in the activation of small molecules, particularly in the reduction of carbon monoxide (CO) and carbon dioxide (CO 2 ). This review examines five decades of progress in the synthesis of metalloformyl complexes and investigations into their structure and reactivity. The bonding in the M–CHO unit is best described as a resonance hybrid between a classical σ-bound formyl ligand and an oxycarbene-like electronic structure, which governs their distinctive spectroscopic signatures and versatile reactivity. Established synthetic routes are summarized, including pathways involving hydride addition and CO insertion, alongside a discussion of the thermodynamic and kinetic factors that control formyl stability. Decomposition pathways and Lewis-acid stabilization strategies are analyzed as key design principles for extending metalloformyl lifetimes under catalytic conditions. Particular attention is given to hydride transfer processes and the role of metalloformyl intermediates as both reactive substrates and hydride sources in reduction chemistry. Lastly, emerging catalytic strategies that exploit metalloformyl intermediates in CO 2 and CO reduction are evaluated, highlighting how control of hydricity, redox potential, and secondary-sphere interactions enables selective C—H bond formation under comparatively mild conditions. Collectively, these studies establish metalloformyl complexes as mechanistically informative and functionally relevant intermediates that bridge fundamental organometallic chemistry with modern approaches to small-molecule activation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Reduction kinetics of hercynite redox materials for solar thermochemical water splitting

Solar thermochemical water splitting (STWS) using a hercynite redox cycle is a promising technology for producing renewable H 2 . Here, the reduction kinetics of hercynite (FeAl 2 O 4 ) is evaluated using thermogravimetric and XRD analyses. The results indicate that as-prepared hercynite materials undergo reduction via two different reaction mechanisms. The reaction first proceeds by a nucleation and growth mechanism (AE1), followed by a third-order kinetic model (F3). XRD analyses show the occurrence of superstoichiometric oxygen in the spinel structure of FeAl 2 O 4+δ in the second reaction mechanism, which indicates the formation of cationic vacancies. TGA and XRD analyses confirm that hercynite maintains its spinel structure when the materials are thermally reduced and oxidized with steam. Differential scanning calorimetry (DSC) performed on FeAl 2 O 4 particles shows two heats of reaction in agreement with the two observed mechanisms. This is the first kinetics study to report on the thermal reduction of hercynite.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Laminar drag reduction in microchannels with liquid infused textured surfaces

Liquid infused surfaces (LIS) achieve non-wetting properties through asperity structures containing pockets of a lubricating liquid rather than air. Although studies have demonstrated several potential applications of LIS, the effect of liquid infused texture on the flow of liquid in microchannels has not been systematically addressed. The present work focuses on the effect of liquid-infused texture geometry and the infused liquid properties on the flow characteristics of a bulk fluid in rectangular and round microchannel geometries. Considering four different textured geometries of transverse ridges, longitudinal ridges, in-lined square posts and staggered squares, a detailed parametric study is presented to assess the resulting drag reduction and friction factor, expressed in terms of the Poiseuille number, on the flow in microchannels. The effect of geometrical parameters is investigated for different asperity solid fraction (Φ s ), asperity height (h s ) and channel thickness (H) or tube diameter (D), while the effect of the infused fluid is studied in terms of a ratio of its viscosity relative to the viscosity of the flowing bulk fluid. Based on the results of the parametric study an extension of the conventional Moody diagram for non-wetting surfaces is developed. Finally, a design of experiments study is conducted to relate the drag reduction and Poiseuille number to the various governing parameters, using which conditions that maximize drag reduction are identified.

42 ENGINEERING↗
DOE OSTI2020

Operator inference for non-intrusive model reduction of systems with non-polynomial nonlinear terms

Here in this work we present a non-intrusive model reduction method to learn low-dimensional models of dynamical systems with non-polynomial nonlinear terms that are spatially local and that are given in analytic form. In contrast to state-of-the-art model reduction methods that are intrusive and thus require full knowledge of the governing equations and the operators of a full model of the discretized dynamical system, the proposed approach requires only the non-polynomial terms in analytic form and learns the rest of the dynamics from snapshots computed with a potentially black-box full-model solver. The proposed method learns operators for the linear and polynomially nonlinear dynamics via a least-squares problem, where the given non-polynomial terms are incorporated on the right-hand side. The least-squares problem is linear and thus can be solved efficiently in practice. The proposed method is demonstrated on three problems governed by partial differential equations, namely the diffusion–reaction Chafee–Infante model, a tubular reactor model for reactive flows, and a batch-chromatography model that describes a chemical separation process. The numerical results provide evidence that the proposed approach learns reduced models that achieve comparable accuracy as models constructed with state-of-the-art intrusive model reduction methods that require full knowledge of the governing equations.

42 ENGINEERING↗
DOE OSTI2021

Skeletal model reduction with forced optimally time dependent modes

Skeletal model reduction based on local sensitivity analysis of time dependent systems is presented in which sensitivities are modeled by forced optimally time dependent (f-OTD) modes. The f-OTD factorizes the sensitivity coefficient matrix into a compressed format as the product of two skinny matrices, i.e. f-OTD modes and f-OTD coefficients. The modes create a low-dimensional, time dependent, orthonormal basis which capture the directions of the phase space associated with most dominant sensitivities. These directions highlight the instantaneous active species, and reaction paths. Evolution equations for the f-OTD modes and coefficients are derived, and the implementation of f-OTD for skeletal reduction is described. For demonstration, skeletal reduction is conducted of the constant pressure ethylene-air burning in a zero-dimensional reactor, and new reduced models are generated. The laminar flame speed, the ignition delay, and the extinction curve as predicted by the models are compared against some existing skeletal models in literature for the same detailed model. Finally, the results demonstrate the capability of f-OTD to eliminate unimportant reactions and species in a systematic, efficient and accurate manner.

42 ENGINEERING↗
DOE OSTI2023

Control oriented model order reduction for the hydraulic system of an autonomous wheel loader

Control design for an autonomous wheel loader requires a high-fidelity and low-order dynamics model. The objective of order reduction is to decrease the number of states in the model while maintaining performance comparable to the original model. Of all the power components in a wheel loader, the model order reduction for steering and working hydraulic systems is most demanding due to its nonlinear and stiff dynamical nature. This paper describes a physics-inspired model order reduction method that can reduce the model order by close to thirty percent. It is achieved by discarding orders with fast dynamics and consolidating multiple states into less new states. Furthermore, this method can also be extended to other types of off-road vehicles such as excavators, bulldozers, etc. Simulation results demonstrate that the reduced-order model exhibits very similar performance to the full-order model under typical operating conditions of wheel loaders, with an output error of less than six percent.

42 ENGINEERING↗
DOE OSTI2023

Demand reduction and energy saving potential of thermal energy storage integrated heat pumps [Réduction de la demande et potentiel d'économie d'énergie des pompes à chaleur avec stockage d'énergie thermique intégré]

A heat pump (HP) moves heat from a low-temperature source to a high-temperature sink with an input of energy. Often, one temperature body fluctuates with time (e.g., diurnal ambient temperature), causing the HP efficiency to vary. Integrating thermal energy storage (TES) into a HP system adds a third temperature body, enabling the HP to be advantageously coupled to any two: the application, the ambient, or the TES at strategic times. Although TES integration with HPs is an important emerging technology to lower energy consumption and decrease energy demand during critical times, the favorable circumstances for TES integration are poorly understood. Here, this paper establishes the energy reduction and demand reduction potential of TES-integrated HPs with both analytical and numerical HP models. All possible temperature arrangements are considered for HP-TES systems with two fixed temperature bodies (application and TES) and one variable temperature (ambient). Results show that overall energy savings are most attainable when the TES temperature is near the application temperature, whereas a large temperature difference between the TES and the application leads to the most peak demand reduction. The potential for overall energy savings increases as the magnitude of ambient temperature fluctuations increases.

25 ENERGY STORAGE↗
DOE OSTI2020

Discrete ordinates analysis of the forced-flight variance reduction technique in Monte Carlo neutral particle transport simulations

This paper presents mathematical formulations and methods to predict the effect of forced-flight variance reduction on Monte Carlo tally variance and calculation time. This includes deducing biasing operators that are then used to construct a history-score probability density function (HSPDF), which represents all possible Monte Carlo random walks and gives the probability of a Monte Carlo history scoring in a tally from a particular phase-space position. The history-score moment equations (HSMEs), the statistical moments of the HSPDF, are then derived to calculate the statistical behavior of the Monte Carlo tally when forced-flight variance reduction is applied. In addition, the future-time equation (FTE) is derived to predict the Monte Carlo computational time as a result of applying forced-flight variance reduction. The solutions of the HSMEs and FTE can be used to predict Monte Carlo computational cost. Furthermore, this work also describes a discrete ordinates method to solve the forced-flight HSMEs and FTE. Several 1-D and 2-D test problems verify that the derivations are performed and implemented correctly.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

A hybrid Monte Carlo-deterministic second moment method with efficient variance reduction

In this work, we present a hybrid method that combines Monte Carlo with deterministic finite element methods to solve a linear Boltzmann transport equation. Our hybrid method runs orders of magnitude faster than Monte Carlo, without sacrificing accuracy, for a proxy problem from radiative transfer that contains both optically-thick and optically-thin material. We believe that this is the first demonstration of a hybrid Second Moment Method in more than one spatial dimension, the first to consider more than one material, and the first to use variance reduction. Our variance reduction approach arises from an asymptotic analysis in which we show that the magnitude of the scattering source grows without bound. We transform the problem to compute the deviation of the radiation intensity from isotropy. The magnitude of the source in the transformed problem is bounded, and the quality of the hybrid method solution is dramatically improved by a substantial reduction in the variance.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗