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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Insights into coordination and ligand trends of lanthanide complexes from the Cambridge Structural Database

Abstract Understanding lanthanide coordination chemistry can help develop new ligands for more efficient separation of lanthanides for critical materials needs. The Cambridge Structural Database (CSD) contains tens of thousands of single crystal structures of lanthanide complexes that can serve as a training ground for both fundamental chemical insights and future machine learning and generative artificial intelligence models. This work aims to understand the currently available structures of lanthanide complexes in CSD by analyzing the coordination shell, donor types, and ligand types, from the perspective of rare-earth element (REE) separations. We obtain four sets of lanthanide complexes from CSD: Subset 1, all Ln-containing complexes (49472 structures); Subset 2, mononuclear Ln complexes (27858 structures); Subset 3, mononuclear Ln complexes without cyclopentadienyl ligands (Cp) (26156 structures); Subset 4, Ln complexes with at least one 1,10-phenanthroline (phen) or its derivative as a coordinating ligand (2226 structures). The subsequent analysis of lanthanide complexes in these subsets examines the trends in coordination numbers and first shell distances as well as identifies and characterizes the ligands and donor groups. In addition, examples of Ln-complexes with commercially available complexants and phen-based ligands are interrogated in detail. This systematic investigation lays the groundwork for future data-driven ligand designs for REE separations based on the structural insights into the lanthanide coordination chemistry.

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

Thermocouple Testing in Support of the AGR-5/6/7 Experiment

This report documents thermocouple testing performed in IRC Lab C-15 over a period of seven years. This testing supported selection and characterization of the thermocouple set used in the AGR-5/6/7 experiment. The following summary was taken directly from the report. Temperature measurement is a challenging aspect of very high temperature irradiation experiments because commonly used high-temperature commercial thermocouples such as platinum-rhodium (Types S, R, and B) and tungsten-rhenium (Type C), suffer dramatic drift because of neutron-induced transmutation. As a result, these types of thermocouples, which are used routinely for industrial temperature measurements outside of reactors, are used only in very special circumstances for reactor experiments. Conversely, because of their low neutron cross-sections, Type N thermocouples are affected to only a limited extent by neutron irradiation. However, the use of these nickel-based thermocouples is limited when the temperature exceeds 1050°C due to drift arising from minor alloying elements migrating from the thermocouple's metal sheath to the thermoelements. This change in the composition of the thermo-elements results in significant decalibration of the signal. The issues described above were recognized during the early planning stages of the final AGR experiment (designated AGR-5/6/7), and a thermocouple furnace testing program was performed over a seven-year period (2014-2019, 2021) to first select and then characterize the best thermocouple set for the high temperature regions of the AGR-5/6/7 irradiation experiment. The calculated temperature range of the AGR-5/6/7 experiment was 600–1500°C. For temperatures below 1000°C standard Type N thermocouples were deemed adequate. The furnace testing campaign identified two thermocouple types suitable for measuring temperatures above 1000°C, a Mo/Nb thermocouple developed at INL called HTIR-TC, and a Type N thermocouple developed by Cambridge University (called herein Cambridge Type N), which featured a custom high nickel alloy sheath. One of the original goals of the furnace testing program was to identify a thermocouple capable of low drift operation near the peak temperature expected in AGR-5/6/7, i.e., about 1400°C. The HTIR-TC design appeared promising in this regard, however a manufacturing difficulty proved to be a barrier and instead the furnace testing focused on drift performance at 1250°C. The manufacturing difficulty was that the Nb sheaths of the HTIR-TCs experienced extreme embrittlement when heat treated at 1600°C or greater. Heat treatment is needed to stabilize the emf output of this TC type, and the higher the heat treatment temperature the higher the peak temperature of stable operation. Because of the sheath embrittlement the heat treatment temperature had to be lowered to 1450°C resulting in a stable operating temperature of about 1250°C. One of the successes of the furnace testing program was identification of a shortcoming in the heat treatment procedure that had been traditionally used in the production of HTIR-TCs. The shortcoming was that the entire heated length of the HTIR-TC sensor was not being heat treated, but rather only the part of the sensor expected to experience temperatures above 1000°C. The problem manifested itself when the thermocouples were removed from the heat treat furnace and placed in another furnace with a different geometry, their indicated temperatures would be widely scattered, but mostly in the negative direction. The solution was to heat treat the entire heated length of the sensor. Since the deepest immersion depth in the AGR-5/6/7 experiment was about 40 inches, a heat treatment length of 48 inches was used. After this change was implemented, thermocouples which were moved into a new environment with a different temperature profile (i.e., a different furnace), produced accurate temperature measurements. Although assembly of the AGR-5/6/7 experiment was completed in September of 2017 (and irradiation begun in 2018), furnace testing of thermocouples continued in 2018 and 2019. The main purpose of this testing was to establish very long-term drift characteristics of the HTIR and Cambridge Type N thermocouples installed in the experiment. Representative thermocouples from the same lots as those installed in the AGR-5/6/7 experiment were used. Additionally, thermocouples of different designs, (particularly variations on the HTIR-TC design) were "piggy-backed" on this testing program to provide insights for instrumenting future very high temperature irradiation experiments. This two-year testing program demonstrated that HTIR-TCs and Cambridge Type N TCs could operate at 1250°C for up to 10,000 hrs (and in some cases longer) while experiencing negative drifts on the order of 2-4°C/1000 hrs. This performance was considered acceptable given the extreme operating environment the sensors faced.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Closures for multicomponent reacting flows based on dispersion analysis

This work presents algebraic closure models associated with advective transport and nonlinear reactions in a Reynolds-averaged Navier-Stokes context for a system of species subject to binary reactions and transport by advection and diffusion. Expanding upon analysis originally developed for non-reactive transport in the context of Taylor dispersion of scalars, this work extends the modified gradient diffusion model explicated by Peters [N. Peters, Turbulent Combustion, Cambridge Monographs on Mechanics (Cambridge University Press, Cambridge, 2000)] and based on work by Corrsin [S. Corrsin, The reactant concentration spectrum in turbulent mixing with a first-order reaction, J. Fluid Mech. 11, 407 (1961)] beyond single-component transport phenomena and involving nonlinear reactions. The presented model forms, from this weakly nonlinear extension of the original dispersion theory, lead to an analytic expression for the eddy diffusivity matrix that explicitly captures the influence of the reaction kinetics on the closure operators. Furthermore, we demonstrate that the derived model form directly translates between flow topologies through a priori and a posteriori testing of a binary species system subject to homogeneous isotropic turbulence. Using two- and three-dimensional direct numerical simulations involving laminar and turbulent flows, it is shown that this framework improves prediction of mean quantities compared to previous results. Lastly, the presented model form, collapses to the earlier gradient diffusion and its modified version derived by Corrsin in the limits of nonreactive species and linear reactions, respectively.

42 ENGINEERING↗
DOE OSTI2023

Advanced Modeling and Simulation Methods for Evaluation of Thermal Neutron Scattering Materials

With the rise of interest in thermal neutron scattering data for advanced reactor, criticality safety, and shielding applications, new experimental data are required for evaluation of new materials or for re-evaluation (or validations) of previously evaluated materials. New experimental data are evaluated in a three-step process: (1) computing the phonon characteristics, (2) computing the dynamic structure factor (DSF) from the data, and (3) using the experimental setup to simulate the experimental data. All three steps have challenges, ranging from the need for a sufficiently general material simulation code—a processing code that can compute the corresponding DSF—to having a detailed layout of the instrument/beamline/facility where the data were measured. Whereas phonon characteristics of materials can be computed using various methods (molecular dynamics, density functional theory, etc.), a high-fidelity computation of the DSF and the simulation of the experiment based on the DSF is vital to the accuracy of the evaluation. The latter two steps can be achieved by using the two corresponding code systems developed by instrument scientists at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory: (1) OCLIMAX, a program that calculates the dynamic structure factor from DFT and MD simulation results, and (2) MCViNE, a Monte Carlo neutron ray-tracing program designed to simulate neutron scattering experiments. Recently, polyethylene and yttrium hydride were measured at the Wide Angular-Range Chopper (ARCS) and SEQUOIA instrument stations of the SNS. These experiments are simulated using the density functional theory code, the Cambridge Serial Total Energy Package (CASTEP), to compute its phonon characteristics (eigenvalues/vectors and PDOS), which is then processed using OCLIMAX to yield the DSF, and finally the data at each instrument station are simulated by the MCViNE for comparison to the measured data for evaluation. For comparison to conventional evaluation methods, the scattering data processed from OCLIMAX are compared against those processed from the LEAPR module of NJOY, and the results from MCViNE simulations are compared against previously used simplified beamline models implemented in the Monte Carlo N-Particle (MCNP) code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Development and Test Results of Thermocouples Used in the TRISO-Fuel Irradiation Experiment AGR-5/6/7

High-temperature gas reactor irradiation experiments create unique challenges for thermocouple-based temperature measurements. High-temperature industrial thermocouples suffer rapid decalibration due to transmutation of the thermoelements from neutron absorption. For lower-temperature applications, Type K and Type N thermocouples are affected by neutron irradiation only to a limited extent. But until recently, the use of these nickel-based thermocouples was limited when the temperature exceeded 1050°C due to drift related to phenomena other than nuclear irradiation. Certain portions of the AGR-5/6/7 experiment experienced temperatures higher than any of the previous AGR tests, up to 1500°C. Recognizing the limitations of existing thermometry to measure such high temperatures, the sponsor of the AGR-5/6/7 test supported a development and testing program for thermocouples capable of low-drift operation at temperatures above 1100°C. This program included additional development of high-temperature irradiation-resistant thermocouples based on molybdenum/niobium thermoelements, which have been studied at Idaho National Laboratory since circa 2004. A step change in accuracy and long-term stability of this thermocouple type was achieved as part of the AGR-5/6/7 thermometry development program. Additionally, long-term testing (7000+ h) at 1250°C of Type N thermocouples utilizing a customized sheath developed at the University of Cambridge has been completed with excellent low-drift results. The results of this testing as well as testing of the improved high-temperature irradiation-resistant design are reported herein. Both the improved high-temperature irradiation-resistant and the Cambridge Type N thermocouple types were incorporated into the AGR-5/6/7 test, which began irradiation in February 2018 and was completed in July 2020. Finally, a summary of the performance of the thermocouples incorporated into the AGR-5/6/7 test is included herein.

In-pile instrumentation↗
DOE OSTI2020

SolSmart Webinar - Community Choice Aggregation & Solar Development

This webinar focuses on community choice aggregation (CCA) as a potential strategy for local governments to achieve their clean energy goals. The webinar provides an overview of what CCA is, how it works, and considerations for local governments interested in establishing or participating in a CCA program. The webinar will highlight case studies from CCAs across the U.S. that support local renewable energy development. This webinar provides one AICP CM continuing education credit. Who: Ben Butterwoth, Senior Associate, The Cadmus Group; Megan Lynch, Analyst, The Cadmus Group; Jenna Famular, Communications Manager, MCE Clean Energy; Meghan Shaw, Outreach Director for Cambridge Energy Alliance, City of Cambridge; Daniel Falk, Project Manager, The Solar Foundation

14 SOLAR ENERGY↗
DOE OSTI2022

Structural Flexibility of Metal Chelate Complexes and Its Relation to Supramolecular Chemistry

In this study, crystal structures of metal chelate and related complexes in the Cambridge Structural Database have been analyzed, with respect to their use as components in supramolecular metal-organic compounds. In β-diketonate complexes, the distribution of angles between ligands is relatively broad; other ligands, such as 2,2'-bipyridine, yield significantly narrower distributions. According to the principle of structure correlation, these distributions reflect the ease of distorting the various families of complexes. A comparison through density functional theory calculations also indicates that angular distortions require significantly less energy for M(β-diketonate) 3 than for M(2,2'-bipyridine) 3 . The differences are likely to affect the construction of supramolecular systems from different combinations of metals and ligands, including the likelihood that the desired structures will be obtained.

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

Jet fragmentation function and groomed substructure of bottom quark jets in proton-proton collisions at 5.02 TeV

A measurement of the substructure of bottom quark jets (b jets) in proton-proton (pp) collisions is presented. The measurement uses data collected in pp collisions at $\sqrt{s}=5.02$ TeV, with a low number of simultaneous interactions per bunch crossing, recorded by the CMS experiment in 2017, corresponding to an integrated luminosity of 301 pb −1 . An algorithm to identify and cluster the charged decay daughters of b hadrons is developed for this analysis, which facilitates the exposure of the gluon radiation pattern of b jets using iterative Cambridge-Aachen declustering. The soft-drop-groomed jet radius, R g , and momentum balance, z g , of b quark jets are presented. These observables can be used to test perturbative quantum chromodynamics predictions that account for mass effects. Because the b hadron is partially reconstructed from its charged decay daughters, only charged particles are used for the jet substructure studies. In addition, a jet fragmentation function, z b,ch , is measured, which is defined as the distribution of the ratio of the transverse momentum (p T ) of the partially reconstructed b hadron with respect to the charged-particle component of the jet p T . The substructure variable distributions are unfolded to the charged-particle level. The b jet substructure is compared to the substructure of jets in an inclusive jet sample that is dominated by light-quark and gluon jets in order to assess the role of the b quark mass. A strong suppression of emissions at small R g values is observed for b jets when compared to inclusive jets, consistent with the dead-cone effect. The measurement is also compared with theoretical predictions from Monte Carlo event generators. This is the first substructure measurement of b jets that clusters together the b hadron decay daughters independent of the b hadron species and decay channel.

boosted jets↗
DOE OSTI2026

Exploring small-angle emissions in charm quark jets in proton-proton collisions at $\sqrt{s}=5.02$ TeV

A measurement of the angular structure of inclusive jets and those containing a prompt D 0 meson in proton-proton collisions at the LHC at a center-of-mass energy of 5.02 TeV is presented. The data corresponding to an integrated luminosity of 301 pb −1 were collected by the CMS experiment in 2017. Two jet grooming algorithms, late-k T and soft drop, are used to study the intrajet radiation pattern using iterative Cambridge-Aachen declustering. The splitting-angle distributions of jets with transverse momentum (p T ) of around 100 GeV, obtained with these two algorithms, show that there is a shift of the distribution for jets containing a prompt D 0 meson with respect to inclusive jets. The suppression of emissions at small angles observed in the late-k T grooming approach is consistent with the dead-cone effect, whereas the similar suppression for splittings selected with the soft-drop algorithm appears to be induced by gluon splitting to charm quark-antiquark pairs at large angles. The measured distributions are corrected to the particle level and can be used to constrain model predictions for the substructure of high-p T charm quark jets.

Charm Physics↗
DOE OSTI2022

Predicting the oxidation states of Mn ions in the oxygen-evolving complex of photosystem II using supervised and unsupervised machine learning

Abstract Serial Femtosecond Crystallography at the X-ray Free Electron Laser (XFEL) sources enabled the imaging of the catalytic intermediates of the oxygen evolution reaction of Photosystem II (PSII). However, due to the incoherent transition of the S-states, the resolved structures are a convolution from different catalytic states. Here, we train Decision Tree Classifier and K-means clustering models on Mn compounds obtained from the Cambridge Crystallographic Database to predict the S-state of the X-ray, XFEL, and CryoEM structures by predicting the Mn’s oxidation states in the oxygen-evolving complex. The model agrees mostly with the XFEL structures in the dark S 1 state. However, significant discrepancies are observed for the excited XFEL states (S 2 , S 3, and S 0 ) and the dark states of the X-ray and CryoEM structures. Furthermore, there is a mismatch between the predicted S-states within the two monomers of the same dimer, mainly in the excited states. We validated our model against other metalloenzymes, the valence bond model and the Mn spin densities calculated using density functional theory for two of the mismatched predictions of PSII. The model suggests designing a more optimized sample delivery and illumiation systems are crucial to precisely resolve the geometry of the advanced S-states to overcome the noncoherent S-state transition. In addition, significant radiation damage is observed in X-ray and CryoEM structures, particularly at the dangler Mn center (Mn4). Our model represents a valuable tool for investigating the electronic structure of the catalytic metal cluster of PSII to understand the water splitting mechanism.

Plant Sciences↗
DOE OSTI2020

The mean logarithm emerges with self-similar energy balance.

The attached eddy hypothesis of Townsend (The Structure of Turbulent Shear Flow, 1956, Cambridge University Press) states that the logarithmic mean velocity admits self-similar energy-containing eddies which scale with the distance from the wall. Over the past decade, there has been a significant amount of evidence supporting the hypothesis, placing it to be the central platform for the statistical description of the general organisation of coherent structures in wall-bounded turbulent shear flows. Nevertheless, the most fundamental question, namely why the hypothesis has to be true, has remained unanswered over many decades. Under the assumption that the integral length scale is proportional to the distance from the wall y , in the present study we analytically demonstrate that the mean velocity is a logarithmic function of y if and only if the energy balance at the integral length scale is self-similar with respect to y , providing a theoretical basis for the attached eddy hypothesis. The analysis is subsequently verified with the data from a direct numerical simulation of incompressible channel flow at the friction Reynolds number Reτ≃5200 (Lee & Moser, J. Fluid Mech., vol. 774, 2015, pp. 395–415).

42 ENGINEERING↗
DOE OSTI2020

Powder X-ray diffraction of fluorometholone, C 22 H 29 FO 4

Commercial fluorometholone, CAS #426-13-1, crystallizes in the monoclinic space group P 2 1 (#4) with a = 6.40648(2), b = 13.43260(5), c = 11.00060(8) Å, β = 92.8203(5)°, V = 945.517(5) Å 3 , and Z = 2. A reduced cell search in the Cambridge Structural Database yielded one previous structure determination, using single-crystal data at 292 K. In this work, the sample was ordered from the United States Pharmacopeial Convention (Lot # R032K0) and analyzed as-received. The room temperature (295 K) crystal structure was refined using synchrotron ( λ = 0.412826 Å) powder diffraction data and optimized using density functional theory (DFT) techniques. Hydrogen positions were included as a part of the structure and were re-calculated during the refinement. The diffraction data were collected on beamline 11-BM at the Advanced Photon Source, Argonne National Laboratory, and the powder X-ray diffraction pattern of the compound has been submitted to ICDD® for inclusion in the Powder Diffraction File™. The agreement of the Rietveld-refined and DFT-optimized structures is excellent; the root-mean-square Cartesian displacement is 0.060 Å. In addition to the O–H⋯O hydrogen bonds observed by Park et al. (Park, Y. J., Lee, M. Y., and Cho, S. I. ( 1992 ). “Fluorometholone,” J. Korean Chem. Soc. 36 , 812–817), C–H⋯O hydrogen bonds contribute to the crystal energy.

Gonzalez, Diana↗
DOE OSTI2024

Trust Not Verify? The Critical Need for Data Curation Standards in Materials Informatics

The importance of data curation has been recognized in multiple areas of research; however, the discussion of this important issue is only beginning to emerge in materials science. In this Perspective, we highlight the benefits of using the standardized data curation protocols in materials science and discuss current gaps in accurate and reproducible data reporting using case studies drawn from high-impact materials science papers and well-known databases such as the Crystallography Open Database (COD) and the Cambridge Structural Database (CSD). We argue that both experimental and computational materials scientists need to embrace a culture of rigorous data curation as part of modern research data management. We propose a sample data curation pipeline for materials chemistry and illustrate its use by creating two new materials chemistry databases. Here, we hope that this perspective will serve to catalyze further discussion and promote the continuous development of rigorous data curation practices within the materials science research community. We posit that adherence to best practices of data curation will promote and enhance the reliability, reproducibility, and integrity of materials research and enable the development of reliable AI and machine learning models that critically depend on the use of quality data.

Chemical structure↗
DOE OSTI2021

Predicting Energetics Materials’ Crystalline Density from Chemical Structure by Machine Learning

To expedite new molecular compound development, a long-sought goal within the chemistry community has been to predict molecules’ bulk properties of interest a priori to synthesis from a chemical structure alone. In this work, we demonstrate that machine learning methods can indeed be used to directly learn the relationship between chemical structures and bulk crystalline properties of molecules, even in the absence of any crystal structure information or quantum mechanical calculations. We focus specifically on a class of organic compounds categorized as energetic materials called high explosives (HE) and predicting their crystalline density. An ongoing challenge within the chemistry machine learning community is deciding how best to featurize molecules as inputs into machine learning models—whether expert handcrafted features or learned molecular representations via graph-based neural network models—yield better results and why. We evaluate both types of representations in combination with a number of machine learning models to predict the crystalline densities of HE-like molecules curated from the Cambridge Structural Database, and we report the performance and pros and cons of our methods. Our message passing neural network (MPNN) based models with learned molecular representations generally perform best, outperforming current state-of-the-art methods at predicting crystalline density and performing well even when testing on a data set not representative of the training data. However, these models are traditionally considered black boxes and less easily interpretable. Here, to address this common challenge, we also provide a comparison analysis between our MPNN-based model and models with fixed feature representations that provides insights as to what features are learned by the MPNN to accurately predict density.

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

Curated Collection of More than 20,000 Experimentally Reported One-Dimensional Metal–Organic Frameworks

Herein, a collection of more than 20,000 experimentally derived crystal structures for metal–organic frameworks (MOFs) that do not have two- or three-dimensional covalently bonded networks has been developed from the materials available at the Cambridge Crystallographic Data Centre. Of these 20,000 1D MOFs, more than 12,000 structures have been verified to be solvent-free and in exact agreement with the stoichiometry of the synthesized materials. More than 10% of the complete data set comprise materials including two or more distinct metals. The band gaps of more than 12,000 1D MOFs have been computed at the density functional theory-generalized gradient approximation level, finding more than 2000 materials that have a zero band gap. Molecular simulations of CH4 adsorption in a small number of 1D MOFs indicated that adsorbate-induced deformation plays a significant role in determining adsorption isotherms in these materials. As a result, methods that have been used previously for high-throughput predictions of molecular adsorption in 3D MOFs are not suitable for 1D MOFs.

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

A Review of Computational Models for the Flow of Milled Biomass Part II: Continuum-Mechanics Models

The design of efficient material-handling systems for milled lignocellulosic biomass is challenging due to their complex particle morphologies and frictional interactions. Computational modeling, including the discrete element method (DEM) and continuum-based finite-element/volume methods, may offer scientific insight and predictive capabilities for the flow of milled biomass in hoppers and feeders. Herein, this article (Part II) presents a review of current state-of-the-art continuum models for the flow of milled biomass, whereas DEM models are reviewed in a companion article (Part I). Advances of numerical methods to solve the global governing equations are discussed first, followed by a comprehensive review of constitutive models for granular materials, including Drucker–Prager, hypoplastic, Cambridge-type, inertial-rheology, and nonlocal granular fluidity models. Specifically, we provide in-depth discussion on the suitability of those models for milled lignocellulosic biomass materials in terms of nonlinear elasticity, dependence of flow strength on pressure, density and shear rate, and compaction (dilation) associated with hardening (softening). Furthermore, our study shows that, despite the recent advances in continuum granular flow modeling, the most suitable constitutive models still need further development to account for material parametrization, multiflow regimes, and multiscale behavior before they can be reliably used to optimize the design and operation of biomass handling systems.

09 BIOMASS FUELS↗
DOE OSTI2021

Learning the structure of wind: A data-driven nonlocal turbulence model for the atmospheric boundary layer

In this work, we develop a novel data-driven approach to modeling the atmospheric boundary layer. This approach leads to a nonlocal, anisotropic synthetic turbulence model which we refer to as the deep rapid distortion (DRD) model. Our approach relies on an operator regression problem that characterizes the best fitting candidate in a general family of nonlocal covariance kernels parameterized in part by a neural network. This family of covariance kernels is expressed in Fourier space and is obtained from approximate solutions to the Navier–Stokes equations at very high Reynolds numbers. Each member of the family incorporates important physical properties such as mass conservation and a realistic energy cascade. The DRD model can be calibrated with noisy data from field experiments. After calibration, the model can be used to generate synthetic turbulent velocity fields. To this end, we provide a new numerical method based on domain decomposition which delivers scalable, memory-efficient turbulence generation with the DRD model as well as others. We demonstrate the robustness of our approach with both filtered and noisy data coming from the 1968 Air Force Cambridge Research Laboratory Kansas experiments. Using these data, we witness exceptional accuracy with the DRD model, especially when compared to the International Electrotechnical Commission standard.

17 WIND ENERGY↗
DOE OSTI2020

Chris Freeman forging the evolution of evolutionary economics

Abstract Every Schumpeterian is an evolutionary economist in his or her own way. Chris Freeman, whose 1995 essay is published in this issue of ICC, favored a rare combination of the Cambridge tradition, a Marxian view of inequalities and Schumpeter’s fascination with innovation as the driving force of capitalism. The article summarizes and discusses this combination and how Freeman generated a challenging agenda for contemporary economics, namely in the context of long wave analysis, the theme for his last book.

Louçã, Francisco↗