SEARCH · Engineering Papers

Results for “continuous improvement”

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.

SourceResearch connectionFrom yearThrough year

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

At least 865 records · Page 48

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Experimental demonstration of high-temperature (>1000 °C) heat extraction from a moving-bed oxidation reactor for thermochemical energy storage

Previously developed reduction-oxidation (redox) thermochemical energy storage technologies must store their products at high temperatures, complicating handling and transportation. This work describes a countercurrent, tubular, moving bed oxidation reactor at laboratory scale that produces high grade heat and allows solids to enter and exit the system at ambient temperatures. The particles implemented in the system consist of a novel magnesium manganese-oxide material well-suited for thermochemical energy storage. Output heat is obtained via a separate extraction gas flow, which exits from the middle portion of the main reactor tube. With this design, reactor temperatures in excess of 1000°C and extraction temperatures above 950°C were achieved. Deviation between the two measurements is a result of extraction thermocouple placement and losses in the reactor extraction arm; improvements to these parameters would bring the extraction temperature closer to the bed temperature. The reactor produces enough energy via oxidation to sustain both heat extraction and continued chemical reaction. During one representative steady state experiment at a particle flow rate of 1.5 g/s, an average of 447 W was extracted from the reactor out of an estimated 1083 W of released chemical energy for a duration of 70 minutes. Among the four experiments, the maximum bench-scale oxidation reactor energy efficiency of 36.2% and corresponding round-trip efficiency of 13.7% considering both redox reactors were demonstrated. Characteristics of an ideal system are considered and future improvements are proposed.

25 ENERGY STORAGE↗

DOE OSTI2021

Improved Self-Assembly of P3HT with Pyrene-Functionalized Methacrylates

A block copolymer with discotic liquid crystalline behavior was synthesized using Grignard metathesis polymerization (GRIM) and initiators for continuous activator regeneration atom transfer radical polymerization (ICAR-ATRP). A novel discotic liquid crystalline mesogen, 6-(pyren-1-yloxy)hexyl methacrylate (PyMA), comprises a block that is attached to regioregular poly(3- hexylthiophene) (rr-P 3 HT) generated by GRIM and subjected to end-group modification. Due to the continuous regeneration of Cu + in the reaction mixture in ICAR-ATRP compared to conventional methods, the synthesis was successfully performed with less catalyst. The purity and yield of the final product are increased by eliminating rigorous post-synthesis purification. Stacked pyrene units have contributed to the enhanced long-range π-π interactions and aligning of the P 3 HT block as observed in thin-film X-ray diffraction (XRD). Furthermore, field-effect mobilities in the order of 10 -2 cm 2 V -1 s -1 in bottom-gate, top-contact organic field-effect transistors (OFETs) suggest an enhancement in charge transport due to the discotic electron-rich pyrene units that help mitigate the insulating effect of the methacrylate backbone. The formation of uniform microdomains of P 3 HT-bpoly(PyMA) observed with tapping mode atomic force microscopy (TMAFM) on the channel regions of OFETs indicates the unique packing of the block copolymer in comparison to pristine P 3 HT. Thermotropic properties of the novel discotic mesogen in the presence and absence of P3HT were observed with both the poly(3-hexylthiophene)-b-poly(6-(pyren-1-yloxy)hexyl methacrylate) (P3HT-b-poly(PyMA)) block copolymer and poly(6-(pyren-1-yloxy)hexyl methacrylate) (poly(PyMA)) homopolymer using polarized optical microscopy (POM) and differential scanning calorimetry (DSC).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Improved band gaps and structural properties from Wannier–Fermi–Löwdin self-interaction corrections for periodic systems

The accurate prediction of band gaps and structural properties in periodic systems continues to be one of the central goals of electronic structure theory. However, band gaps obtained from popular exchange–correlation (XC) functionals (such as LDA and PBE) are severely underestimated partly due to the spurious self-interaction error (SIE) inherent to these functionals. In this work, we present a new formulation and implementation of Wannier function-derived Fermi–Löwdin (WFL) orbitals for correcting the SIE in periodic systems. Since our approach utilizes a variational minimization of the self-interaction energy with respect to the Wannier charge centers (WCC), it is computationally more efficient than the HSE hybrid functional and other self-interaction corrections that require a large number of transformation matrix elements. Here, calculations on several (17 in total) prototypical molecular solids, semiconductors, and wide-bandgap materials show that our WFL self-interaction correction approach gives better band gaps and bulk moduli compared to semilocal functionals, largely due to the partial removal of self-interaction errors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Learning continuous scattering length density profiles from neutron reflectivities using convolutional neural networks

Interpreting neutron reflectivity (NR) data using ad hoc multi-layer models and physics-based models provides information about spatially resolved neutron scattering length density (NSLD) profiles. Recent improvements in data acquisition systems have allowed acquiring thousands of NR curves in a couple of hours, which has led to a need for automated data analysis tools to interpret NR measurements in real-time. Here, we present a machine learning analysis workflow that uses a series of models, based on a convolutional neural network (CNN), to learn the relation between the NSLDs and the NRs, and subsequently produce continuous NSLD profiles directly from NRs. The usefulness of our CNN-based models is demonstrated by constructing NSLDs from NRs of several films containing homopolymer polyzwitterions and diblock copolymers mixed with different types of salts. Comparisons of the NSLDs with those constructed using ad hoc multi-layer models reveal a very good agreement, suggesting the potential of CNN-based models for real-time automated data analysis of NRs.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Updating the Building Science Advisor (BSA): A Tool to Assist in the Design of Durable Building Envelopes

Predicting the moisture durability of building envelope components remains challenging due to multiple influencing factors, including material selection, assembly positioning, local climate conditions, air tightness, interior environment, and construction quality. Building codes increasingly emphasize energy efficiency through enhanced insulation and tighter envelopes but offer limited guidance on moisture durability considerations. Consequently, builders face uncertainty, particularly as new materials and assemblies enter the market.The Building Science Advisor (BSA) is a free, web-based expert system developed to address these challenges by providing actionable insights into the moisture durability and energy efficiency of both new and retrofit wall designs. Recently updated, we are now providing version 3.0 of the tool. BSA features significant user interface improvements, enhancing navigation and user interaction through a refreshed, intuitive design. Additionally, the tool incorporates a newly developed database containing pre-simulated wall assembly cases, significantly reducing response times and improving the accuracy of moisture durability assessments. Furthermore, the updated BSA includes moisture content as a performance criterion, providing users with a more comprehensive understanding of moisture-related durability risks. These enhancements enable rapid, reliable assessments tailored to specific climate zones and local building practices. BSA continues to offer targeted guidance on wall retrofit scenarios and delivers access to an expanded library of location-specific building science resources.This paper describes these key updates, highlighting the enhanced features, expanded capabilities, and overall improvements to user experience and educational content. The paper includes a demonstration that illustrates how the revised BSA effectively supports practitioners in designing durable, energy-efficient building envelope assemblies.

Salonvaara, Mikael [ORNL] (ORCID:0000000318991554)↗

DOE OSTI2023

Synergic Effects of Surface Chemistry and Applied Potentials on the Kinetics of the Electrocatalytic Oxygen Evolution Reaction in IrO 2

Improving the efficacy of the oxygen evolution reaction (OER) through water oxidation is critical for advancing photoelectrochemical water splitting. Among the catalysts, IrO 2 exhibits a high OER catalytic activity and stability under acidic conditions. The OER mechanism in this system has been a topic of intense research; however, many mechanistic understandings are lacking. In this work, we carried out first-principles calculations with an implicit solvation model at a constant potential to study the OER behavior on the IrO 2 (110) surface. We find that the surface hydrogen coverage has a significant effect on OER kinetics and transition states. We then develop a microkinetics model that accounts for the continuous evolution of both OER activation energy and hydrogen coverage as a function of an applied potential. We show that this inclusion leads to significant improvement in the simulated Tafel plot compared to available experiments. In conclusion, our results point to a complex interplay between surface chemistry and the applied potential on OER kinetics.

08 HYDROGEN↗

DOE OSTI2026

Preparing large area of thermochromic nanocomposite films for smart window application

The challenges posed by high building energy bill necessitate proactive implementation of energy-efficient strategies to minimize the uses of both electricity and heating gas and promote the use of free solar energy sources. "Smart" window films/glass, leveraging thermochromic vanadium dioxide (VO 2 ), offer an adaptive approach to harness solar energy, significantly reducing the thermal load of buildings. This is achieved by reflecting the infrared portion of the solar spectrum through a phase transition in the monoclinic M-phase (M) of VO 2 induced by heating. In this study, a scalable continuous flow synthesis process invented by Argonne was employed to explore a wide parameter space, targeting the controlled synthesis of monoclinic VO 2 (M) nanoparticles with well-controlled sizes and morphologies. Additionally, a doping strategy and surface modifications were utilized for high-throughput tuning of the metal-to-insulator transition temperature. Strategies to enhance the solar modulation properties of VO 2 nanoparticles in polymer films were investigated through (i) morphological transformation from spherical to nanorod structures, (ii) surface modification with low refractive index ligands, and (iii) incorporation of additional thermochromic materials for improved solar energy modulation and aesthetically appealing colors in smart films. Furthermore, the study outlines scaling-up synthesis methods for VO 2 nanoparticles in a continuous flow reactor using hydrazine monohydrate. This comprehensive investigation provides valuable insights into the upscaling synthesis and design of advanced VO 2 /polymer composite smart window films with enhanced functionality, solar energy modulation and visible light transmittance, driving the technology a step close for industrial application.

14 SOLAR ENERGY↗

DOE OSTI2021

New physics in rare B decays after Moriond 2021

Abstract The anomalies in rare B decays endure. We present results of an updated global analysis that takes into account the latest experimental input – in particular the recent results on $$R_K$$ R K and BR $$(B_s \rightarrow \mu ^+\mu ^-)$$ ( B s → μ + μ - ) – and that qualitatively improves the treatment of theory uncertainties. Fit results are presented for the Wilson coefficients of four-fermion contact interactions. We find that muon specific Wilson coefficients $$C_9 \simeq -0.73$$ C 9 ≃ - 0.73 or $$C_9 = -C_{10} \simeq -0.39$$ C 9 = - C 10 ≃ - 0.39 continue to give an excellent description of the data. If only theoretically clean observables are considered, muon specific $$C_{10} \simeq 0.60$$ C 10 ≃ 0.60 or $$C_9=-C_{10} \simeq -0.35$$ C 9 = - C 10 ≃ - 0.35 improve over the Standard Model by $$\sqrt{\Delta \chi ^2} \simeq 4.7\sigma $$ Δ χ 2 ≃ 4.7 σ and $$\sqrt{\Delta \chi ^2} \simeq 4.6\sigma $$ Δ χ 2 ≃ 4.6 σ , respectively. In various new physics scenarios we provide predictions for lepton flavor universality observables and CP asymmetries that can be tested with more data. We update our previous combination of ATLAS, CMS, and LHCb data on BR $$(B_s \rightarrow \mu ^+\mu ^-)$$ ( B s → μ + μ - ) and BR $$(B^0\rightarrow \mu ^+\mu ^-)$$ ( B 0 → μ + μ - ) taking into account the full two-dimensional non-Gaussian experimental likelihoods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Establishing Co‐Continuous Network of Conjugated Polymers and Elastomers for High‐Performance Polymer Solar Cells with Extreme Stretchability

High power conversion efficiency (PCE) and mechanical robustness are prerequisites for wearable applications of organic solar cells (OSCs). However, stretchability of present active systems (i.e., crack-onset strain (COS) < 30%) should be improved. While introducing elastomers into active systems is considered a simple method for improving stretchability, the inclusion of elastomers typically results in a decrease in PCE of the OSC with a limited enhancement in the stretchability due to lack of interconnected electrical and mechanical pathways. In this study, it is developed efficient and intrinsically stretchable (IS)-OSCs with exceptional mechanical robustness, by constructing co-continuous networks of conjugated polymers (D18) and elastomers (SEBS) within active layers. It is demonstrated that the blend film with a specific ratio (40:60 w/w) of D18:SEBS is crucial for forming co-continuous structures, establishing well-connected mechanical and electrical channels. Consequently, D18 0.4 :SEBS 0.6 /L8-BO OSCs achieve 16-times higher stretchability (COS = 126%) than the OSCs based on D18/L8-BO (COS = 8%), while achieving 4-times higher PCE (12.13%) compared to the OSCs based on SEBS-rich active layers (D18 0.2 :SEBS 0.8 /L8-BO, PCE = 3.15%). Furthermore, D18 0.4 :SEBS 0.6 -based IS-OSCs preserve 86 and 90% of original PCEs at 50% strain and after 200 stretching/releasing cycles with 15% strain, respectively, demonstrating the highest mechanical robustness among reported IS-OSCs.

14 SOLAR ENERGY↗

DOE OSTI2023

Carbon Fiber and Polymer Composites

Tooling is an integral part of composites manufacturing. Composite tools, also called ‘soft’ tools, are more easily constructed than ‘hard’ metal tools and, because they are made from materials similar to the manufactured composite part, they can be made in-house and have a good co-efficient of thermal expansion match. However, as the ‘soft’ designation suggests, they are more vulnerable to wear and typically find application in relatively low-volume production. Additive manufacturing of thermoplastics has proven to be a lucrative option that can help improve the tooling functionalities, as it offers more design flexibility. Owing to the inherent nature of additive manufacturing, the possibility of printing sensors within the tool material and at proximity to otherwise inaccessible areas of the tool become a reality. Continuous carbon fiber (CCF)-reinforced three-dimensional (3D) printing of engineering thermoplastics has proven to be a viable option to strengthen a part well beyond the ideal moduli of unmodified thermoplastic. Furthermore, adding nanotubes or graphene to the thermoplastic matrix will also improve both the thermal conductivity and interlaminar shear strength within the tool. Carbon nanotubes (CNTs) and carbon fibers (CFs) are microwave susceptors; exploiting the physics of Joule heating to increase the energy efficiency of tool hardening and cure rates is a core goal of this project. Because of the rapid volumetric heating enabled by the absorption of microwave or radio frequency energy and electromagnetic (EM) annealing presents an attractive opportunity to significantly reduce manufacturing cycle times while improving part performance.

Craps, Matthew G.↗

DOE OSTI2024

Automated Manufacturing of Grid Stiffened Panels with Radically Reduced Tooling

Grid stiffened continuous fiber reinforced composite panels are an attractive option for creating lightweight structures due to the tailorability for various applications and the resulting high specific properties. However, the panel stiffeners and stiffener intersections result in high tooling complexity and correspondingly high cost of implementation. These factors have limited the impact of such structures in the composites industry. Previous research has demonstrated the ability to produce high quality, high aspect ratio beams, representative of individual grid stiffeners, using E-glass/PET comingled tow via direct digital manufacturing. Further, prior preliminary efforts have demonstrated the potential to use the same approach to manufacture grid intersections that have continuous fiber in both directions. To expand on the previous efforts in grid stiffeners produced by direct digital manufacture with radically reduced tooling requirements, this effort compares two methods of providing positioning and consolidation, nozzle vs. roller. Both processes are based on a commingled yarn feedstock. The extrusion through a nozzle has been shown to enable grid intersection control through local variations in applied consolidation and serves as the baseline process. However, this approach requires a continuous placement path to create the complete grid stiffened panel as no mechanism for cutting and restarting has been implemented. Alternatively, a newly developed placement head incorporating cut and refeed, mounted to a 6-axis robot, offers the potential of improved path placement efficiency. The two techniques are used to produce similar grid composite stiffeners to evaluate the effectiveness of producing the grid intersections. Rate of deposition of the two end effectors are compared and the quality of the associated grid stiffeners, and intersections, are determined through measurement of geometry, fiber volume fraction and void fraction.

Engineering↗

DOE OSTI2025

Optimized Illuminance Operation-A Light-Driven Dilution Strategy to Improve Microalgae Biomass Productivity

Periodic dilution is a necessary operation to avoid light limitation due to self-shading as the culture grows dense. However, environmental conditions are constantly changing in outdoor cultivation systems, making it difficult to determine the optimal dilution rate. To address this challenge, this study evaluated a dilution approach based on light penetration to optimize illuminance (OptiLum) in the culture. Biomass concentration was controlled via sensor-feedback directed dilution to ensure that light reaching the bottom of the culture was maintained above the compensation intensity. Under replicated outdoor pond conditions, by keeping the entire culture within a net-positive photosynthetic zone, the OptiLum operation improved the biomass productivities of two top-performing strains, Picochlorum celeri and Tetraselmis striata, by 95 % and 86 %, respectively, compared to conventional semi-continuous batch cultivation. The dilution rate varied daily and was dynamically adjusted based on the light status within the culture, which is concurrently influenced by weather, culture density, and growth rate. The techno-economic analysis showed that the OptiLum operation could reduce biomass production cost by as much as 24 % and 33 % for P. celeri and T. striata, respectively, assuming a low-cost dewatering approach with initial gravity settling of biomass can be realized for both strains. However, a more costly two-stage dewatering strategy, comprising only membranes and centrifuges, may be necessary for non-settling strains, such as P. celeri, which would alternatively increase production costs by 23 % for the OptiLum case. The results demonstrated that the proposed OptiLum operation is a promising approach to improve biomass productivity and lower production cost via weather-responsive and self-adjusting dilution.

09 BIOMASS FUELS↗

DOE OSTI2023

Status of PyGriffin Development for Integration into the NEAMS Workbench

The integration of Griffin into Workbench, by way of the PyGriffin code package, was initiated by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program in FY-2022. PyGriffin was developed as a Python wrapper to Griffin to streamline the complex workflow involving mesh, cross section, and Griffin input generation, code execution, and results postprocessing, by improving user experience with high fidelity neutronics analysis through the Workbench GUI interface. PyGriffin can be used as a standalone application or through the PyARC code suite. FY-2023 saw the continued development of PyGriffin to expand its capabilities including advanced post-processing of simulation results and initial development of the Monte Carlo (MC) cross section generation workflow with the Shift MC code. PyGriffin was also approved for open-source software status in FY-2023, initiating plans to move the code repository into an open location. In addition to PyGriffin development, there were many improvements and developments made in PyARC leading to several software releases (latest version is v2.3.0), but the focus of this report is PyGriffin.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

A discontinuous piecewise polynomial generalized moving least squares scheme for robust finite element analysis on arbitrary grids

A variational approach is developed with a meshless discretization to enable accurate and robust numerical simulation of partial differential equations for meshes that are of poor quality. Traditional finite element methods use the mesh to both discretize the geometric domain and to define the finite element shape functions. The latter creates a dependence between the quality of the mesh and the properties of the finite element basis that may adversely affect the accuracy of the discretized problem. Here, we propose a new approach for defining finite element shape functions that breaks this dependence and separates mesh quality from the discretization quality, which we call discontinuous piecewise polynomial generalized moving least squares (DPP-GMLS). At the core of the approach is a meshless definition of the shape functions, which limits the purpose of the mesh to representing the geometric domain and integrating the basis functions without having any role in their approximation quality. The resulting non-conforming space can be utilized within a standard discontinuous Galerkin framework, providing a rigorous foundation for solving partial differential equations on low-quality meshes. We present a collection of numerical experiments demonstrating our approach in a wide range of settings: strongly coercive elliptic problems, linear elasticity in the compressible regime, and the stationary Stokes problem. We demonstrate convergence for all problems and stability for element pairs for problems which usually require inf-sup compatibility for conforming methods, also referring to a minor modification possible through the symmetric interior penalty Galerkin framework for stabilizing element pairs that would otherwise be traditionally unstable. Mesh robustness is particularly critical for elasticity, and we provide an example that our approach provides a greater than 5 x improvement in accuracy and allows for taking an 8 x larger stable timestep for a highly deformed mesh, compared to the continuous Galerkin finite element method.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Evaluation of Extreme Weather Impacts on Utility-scale Photovoltaic Plant Performance in the United States

The global energy system is undergoing significant changes, including a shift in energy generating technologies to more renewable energy sources. However, the dependence of renewable energy sources on local environmental conditions could also increase disruptions in service through exposures to compound, extreme weather events. By fusing three diverse datasets (operations and maintenance tickets, weather data, and production data), this analysis presents a novel methodology to identify and evaluate performance impacts arising from extreme weather events across diverse geographical regions. Text analysis of maintenance tickets identified snow, hurricanes, and storms as the leading extreme weather events affecting photovoltaic plants in the United States. Statistical techniques and machine learning were then implemented to identify the magnitude and variability of these extreme weather impacts on site performance. Impacts varied between event and non-event days, with snow events causing the greatest reductions in performance (54.5%), followed by hurricanes (12.6%) and storms (1.1%). Machine learning analysis identified key features in determining if a day is categorized as low performing, such as low irradiance, geographic location, weather features, and site size. The analysis improves our understanding of compound, extreme weather event impacts on photovoltaic systems, which can inform planning activities, especially as the industry continues to expand into new geographic and climatic regions around the world.

14 SOLAR ENERGY↗

DOE OSTI2023

Learning subgrid-scale models with neural ordinary differential equations

We propose a new approach to learning the subgrid-scale model when simulating partial differential equations (PDEs) solved by the method of lines and their representation in chaotic ordinary differential equations, based on neural ordinary differential equations (NODEs). Solving systems with fine temporal and spatial grid scales is an ongoing computational challenge, and closure models are generally difficult to tune. Machine learning approaches have increased the accuracy and efficiency of computational fluid dynamics solvers. In this approach neural networks are used to learn the coarse- to fine-grid map, which can be viewed as subgrid-scale parameterization. We propose a strategy that uses the NODE and partial knowledge to learn the source dynamics at a continuous level. Our method inherits the advantages of NODEs and can be used to parameterize subgrid scales, approximate coupling operators, and improve the efficiency of low-order solvers. Numerical results with the two-scale Lorenz 96 ODE, the convection-diffusion PDE, and the viscous Burgers' PDE are used to illustrate this approach.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Role of Coatings as Artificial Solid Electrolyte Interphases on Lithium Metal Self-Discharge

Artificial solid electrolyte interphases have provided a path to improved cycle life for high energy density, next-generation anodes like lithium metal. Although long cycle life is necessary for widespread implementation, understanding and mitigating the effects of aging and self-discharge are also required. In this report we investigate several coating materials and their role in calendar life aging of lithium. We find that the oxide coatings are electronically passivating whereas the LiF coating slows charge transfer kinetics. Furthermore, the Coulombic loss during self-discharge measurements improves with the oxide layers and worsens with the LiF layer. It is found that none of the coatings create a continuous conformal, electronically passivating layer on top of the deposited lithium nor are they likely to distribute evenly through a porous deposit, suggesting that none of the materials are acting as an artificial solid electrolyte interphase. Instead, they likely alter performance through modulating lithium nucleation and growth.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Constraining explosive nucleosynthesis by indirect reaction methods at storage rings using unstable beams in batch mode

Nuclear reaction studies on unstable isotopes can strongly help in improving our understanding of nucleosynthesis in stars. Indirect approaches to determining astrophysical reaction rates are increasingly common-place and undergoing continuous refinement. Of particular interest is the use of such indirect techniques at storage rings, which, among other aspects, allow to recycle rare unstable beams. Here, we propose to investigate the reaction rates of astrophysical interest using indirect methods (surrogate, Trojan horse, etc.) in reverse kinematics at the IMP-CAS storage ring. Long lived radioactive ion beams, produced remotely, can be accelerated, and made to interact with light targets. The proposed reactions are 85 Kr(p, p’γ), 85 Kr(d, pγ), constraining the neutron flux in an s-process branching point, 79 Se(p, p’γ), 79 Se(d, pγ), constraining the temperature in s-process nucleosyntheses, and 59 Fe(d, pγ), constraining core collapse supernovae.

Angelis, G. de [National Inst. of Nuclear Physics ↗