Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “common references”

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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Operation of helium sub-atmospheric multistage cryogenic centrifugal compressor trains: Part 2 – Transient modeling and pump-down path selection

Low-pressure conditions required for operation of helium cryogenic systems below the normal boiling point (i.e. 4.2 K) are established through a transient process, commonly referred to as ‘pump-down’. This process is defined as the transition from pressures above atmospheric conditions to the saturation pressure which corresponds to a specified operational temperature. The FRIB 2 K system consists of five cryogenic centrifugal compressors which are operated in series. Historically, the pump-down process path has been established through empirical methods and system operator experience. Investigation into the pump-down process at FRIB aimed to develop a pump-down methodology which relies on theoretical model predictions rather than empirically developed process paths. Ensuring stable operation during the pump-down process involved application of a centrifugal compressor performance prediction model, which is described in Part 1 of this paper. Compressor performance maps can be directly used to evaluate the stability of a selected pump-down path and anticipate the overall reliability of the selected path. In conjunction with the compressor performance maps, a system pressure model was developed to estimate the transient pressure response during the pump-down process. Lastly, an explicit equation was developed to establish a mass flow rate profile for the pump-down process. Implementation of the presented methodology (including the developed models) allows for the system operator to determine a continuous pump-down path which maintains compressor stability while conforming to overall system capabilities. Altogether, the methodology presented has resulted in simplification of transient pump-down operations and increased the reliability, stability and efficiency of the pump-down process.

Compressor train control↗
DOE OSTI2021

Modeling lattice rotation fields from discrete crystallographic slip bands in superalloys

Here in this work, we investigate the relationship between an intense slip band (ISB) and the zone of large lattice rotations that forms ahead of the tip of the ISB. We develop a crystal plasticity finite element model of a discrete ISB lying within an oligocrystalline assembly and calculate the local crystalline stress and lattice rotation fields generated by the ISB. The calculations demonstrate that, first, a region of severe lattice rotations, commonly referred to as a microvolume, does not form without the ISB, and second, large amounts of accumulated slip in the ISB are required to enlarge the microvolume to sizes and rotation magnitudes observed experimentally. Ahead of the ISB tip, the quintessential plastic zone always forms, but the atypical microvolume forms when non-concentrated and spatially diffuse slip is activated by the ISB-induced stress field. This result suggests that the detrimental ISB/microvolume pair will likely appear in pairs of crystals in which transmission of the slip from the ISB is severely blocked by the grain boundary, a hypothesis that we verify with a few target cases.

36 MATERIALS SCIENCE↗
DOE OSTI2020

DICE-gas turbine compound reheat combined cycle

Coal-fired Direct Injection Carbon Engine – Gas Turbine (DICE-GT) Compound-Reheat Combined Cycle (CRCC), is a combined cycle power plant comprising a multiplicity of coal-fired reciprocating internal combustion engines (RICE), which is commonly referred to by the acronym DICE (Direct Injection Carbon Engine); a natural gas-fired gas turbine (turbine and combustor); a heat recovery steam generator (HRSG); a steam turbine generator; and an integrally geared and intercooled centrifugal air compressor. Finally, the concept uses coal-water slurry/fluid in the DICE and natural gas (or hydrogen) in the gas turbine for unmatched efficiency (well above 50% net LHV) and modularity (block sizes of 120, 240 and 360 MW) with easy adaptability to carbon capture and sequestration with minimal additional cost, complexity and performance hit.

42 ENGINEERING↗
DOE OSTI2023

A machine learning approach for identifying variables associated with risk of developing neutralizing antidrug antibodies to factor VIII

A key unmet need in the management of hemophilia A (HA) is the lack of clinically validated markers that are associated with the development of neutralizing antibodies to Factor VIII (FVIII) (commonly referred to as inhibitors). This study aimed to identify relevant biomarkers for FVIII inhibition using Machine Learning (ML) and Explainable AI (XAI) using the My Life Our Future (MLOF) research repository. The dataset includes biologically relevant variables such as age, race, sex, ethnicity, and the variants in the F8 gene. In addition, we previously carried out Human Leukocyte Antigen Class II (HLA-II) typing on samples obtained from the MLOF repository. Using this information, we derived other patient-specific biologically and genetically important variables. These included identifying the number of foreign FVIII derived peptides, based on the alignment of the endogenous FVIII and infused drug sequences, and the foreign-peptide HLA-II molecule binding affinity calculated using NetMHCIIpan. The data were processed and trained with multiple ML classification models to identify the top performing models. The top performing model was then chosen to apply XAI via SHAP, (SHapley Additive exPlanations) to identify the variables critical for the prediction of FVIII inhibitor development in a hemophilia A patient. Using XAI we provide a robust and ranked identification of variables that could be predictive for developing inhibitors to FVIII drugs in hemophilia A patients. These variables could be validated as biomarkers and used in making clinical decisions and during drug development. The top five variables for predicting inhibitor development based on SHAP values are: (i) the baseline activity of the FVIII protein, (ii) mean affinity of all foreign peptides for HLA DRB 3, 4, & 5 alleles, (iii) mean affinity of all foreign peptides for HLA DRB1 alleles), (iv) the minimum affinity among all foreign peptides for HLA DRB1 alleles, and (v) F8 mutation type.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Modeling the non-Schmid crystallographic slip in MAX phases

We present a crystal plasticity constitutive relation for the description of experimentally observed non-Schmid crystallographic slip in a class of ternary carbides and nitrides commonly referred to as MAX phases. In the constitutive relation, we assume that the evolution of the slip system strength in MAX phases has two components – a classical component that depends on the Taylor cumulative shear strain and a non-Schmid component that depends on the stress normal to the slip plane. The non-Schmid crystal plasticity constitutive relation is then used to carry out finite element simulations of micropillar compression of single crystals of two MAX phases, Ti 2 AlC and Ti 3 AlC 2 . The finite element simulations not only quantitatively predict the stress – strain response of a wide range of crystallographic orientations of the micropillars but also rationalize the non-uniform deformation and the deformed shape of the micropillars observed in the experiments for the two materials. As a result, parametric studies are also carried out to quantify the role of the non-Schmid effect and understand the effects of key experimental parameters on the stress – strain response of the micropillars of the two MAX phases.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Extending wire-arc directed energy deposition using non-gravity aligned (NGA) torch methods

For standard Additive Manufacturing (AM) processes, traditional path planning typically relies on a 2.5-dimensional approach. In wire-arc directed energy deposition (DED), commonly referred to as wire-arc additive manufacturing (WAAM), this 2.5D approach inherently limits final near net shape due to the stair-step effect and restricts the maximum overhang angle achievable without part degradation. To achieve better near net shape and part quality, a 3D planning approach that modulates the tool tip position and angle without process changes is demonstrated in components containing up to 105° of unsupported overhang. The experimental methods are validated with half and fully enclosed cylinder sections containing 90° of overhang. The non-gravity aligned methods are then applied to a commercial WAAM system for a composite tool mold demonstrator part. As a result, the methods developed in this paper enable expansion of WAAM system capabilities to parts containing large overhangs without compromising the net shape or material structure of the resulting parts and without the need for a part positioner.

Additive manufacturing↗
DOE OSTI2026

A physically based mechanical model for Mullins effect in thermoplastic polyurethanes

Despite decades of research, connecting the chemical and physical structure of thermoplastic polyurethanes to their mechanical properties remains highly challenging. Of particular note are their large-deformation and rate-dependent behaviors, which vary greatly with molecular chemistry, including the type and relative content of soft and hard segments. In this work, we develop a physically motivated mechanical theory for predicting the behavior of thermoplastic polyurethanes. The theory incorporates a representation of microstructural evolution during mechanical deformation, which captures the signatures of stress softening over cyclic loading (commonly referred to as the Mullins effect). There are only eight physically motivated fitting parameters, including a direct dependence on the hard segment fraction. The model predicts that increasing the hard segment fraction leads to higher stiffness and greater energy dissipation, in quantitative agreement with published experimental data. Furthermore, we provide a comprehensive analysis of the model and validate its predictions across several independent datasets focused on mechanical characterization. Direct comparisons to experimental data demonstrate its predictive capability on the effect of loading rate, cyclic deformations, and applied tension or compression. Altogether, this work establishes a predictive framework that connects polymer chemistry and microstructure to emergent mechanical behaviors.

36 MATERIALS SCIENCE↗
DOE OSTI2025

High-temperature nanoindentation creep studies on castable and sintered nanostructured low-activation ferritic-martensitic alloys

In this article, we present the creep characteristics of two reduced activation ferritic-martensitic steels of identical starting compositions formed by different fabrication routes: a nanostructured ferritic alloy commonly referred to as a castable nanostructured alloy (CNA) and a sintered nanostructured alloy (SNA) variant. Through a series of nanoindentation experiments spanning a temperature range of 25 °C to 650 °C, with a maximum load of 100 mN, we find creep behaviors in the cast and sintered materials to be remarkably similar. The creep stress exponent (n) for CNA and SNA were found to be in the range of 8–35 and the activation volume was ∼14–42b 3 , underscoring a dominance of dislocation-mediated mechanisms in both alloys. Notably, we observed a decline in the creep stress exponent with increasing temperature, attributable to the heightened influence of thermally activated dislocations. This phenomenon suggests a potential transition in the deformation mechanism towards a thermally activated dislocation climb process, significantly impacting the observed creep behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Realizing "Net-Zero-Carbon" Sustainable Aviation Fuel

The aviation industry needs renewable and fungible jet fuel - commonly referred to as sustainable aviation fuel (SAF) - to minimize emissions and increase efficiencies. SAF can displace the same, if not more, CO2 equivalent emissions (CO2eq), reduce contrail formation, and increase engine-aircraft efficiencies. Flight represents ~10% of transportation greenhouse gas emissions, with the global consumption of ~400 billion liters of fossil jet fuel in 2019 releasing over 900 million tons of CO2eq. Even with impacts from the COVID-19 global pandemic, the aviation sector is projected to grow with passenger miles expected to double by 2050, relative to 2010. As such, there is an urgent need to produce drop-in aviation fuel from renewables with a dramatically lower carbon footprint.

biojet↗
DOE OSTI2021

Microstructural Progression of Shear-Induced Mixing in a CuNi Alloy

Shear deformation has been highlighted in multiple research efforts for its ability to impart mechanical properties improvements and unique microstructures. When used to process and densify powdered material, these shear-based consolidation techniques are commonly referred to as friction consolidation (FC). In this paper, we have examined the microstructural evolution from compacted Cu and Ni powders to a consolidated Cu0.5Ni0.5 alloy. We have shown various stages of porosity reduction and preferential deformation being accommodated by the more ductile material early in the process, leading to formation of a tortuous microstructural zone. Porosity reduction was extensive, decreasing from ~65% in the unprocessed powder to ~1% in the fully consolidated alloy. The final consolidated alloy showed roughly a 2X hardness improvement over the unalloyed, compacted material. Unique aspects of this work include demonstration of the ability to use FC processing to produce a submicron and equiaxed grain size in samples within a 0.5 to 2 minute processing time.

Overman, Nicole R.↗
DOE OSTI2024

2D analysis of tokamak divertor-plasma detachment-bifurcation with operational parameters and geometries

UEDGE simulations with density scans for various input power, transport coefficients and outer poloidal leg length are performed to study the conditions for the existence of a bifurcation-like drop of T e at the outer strike point, commonly referred to as a detachment cliff, when transitioning to a detached plasma from an attached plasma in the outer divertor as the upstream density increases (McLean et al., 2015). The simulation results show that a detachment cliff tends to occur with a higher power input regardless of diffusivities and leg length. Further analysis of change of plasma profiles at a cliff indicate that, in addition to the sharp reduction of the E x B drift fluxes in the outer divertor studied in Jaervinen et al., (2018), the substantial change of the Mach number in the outer divertor and the decrease of the outer mid-plane T e due to the radiation front moving across the separatrix into the confinement region above the X-point consistently occur for all UEDGE density scans that have a detachment cliff. UEDGE time-dependent simulation of the evolution of a detachment cliff shows that the rapid increase of radiation above the X-point occurs in a time scale of ~0.3–0.5, which could possibly be the trigger for the formation of a detachment cliff, quicker than the Mach number change in a time scale of ~1 ms and the drop of T e in a time scale of ~2–3 ms in the outer divertor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

ν-point energy correletors with F AST EEC: Small-x physics from LHC jets

In recent years, energy correlators have emerged as a powerful tool for studying jet substructure, with promising applications such as probing the hadronization transition, analyzing the quark-gluon plasma, and improving the precision of top quark mass measurements. The projected N-point correlator measures correlations between N final-state particles by tracking the largest separation between them, showing a scaling behavior related to DGLAP splitting functions. These correlators can be analytically continued in N, commonly referred to as ν-correlators, allowing access to non-integer moments of the splitting functions. Of particular interest is the ν → 0 limit, where the small momentum fraction behavior of the splitting functions requires resummation. Originally, the computational complexity of evaluating ν-correlators for M particles scaled as 2 2M , making it impractical for real-world analyses. However, by using recursion, we reduce this to M 2M , and through the FastEEC method of dynamically resolving subjets, M is replaced by the number of subjets. This breakthrough enables, for the first time, the computation of ν-correlators for LHC data. In practice, limiting the number of subjets to 16 is sufficient to achieve percent-level precision, which we validate using known integer-ν results and convergence tests for non-integer ν. We have implemented this in an update to FastEEC and conducted an initial study of power-law scaling in the perturbative regime as a function of ν, using CMS Open Data on jets. The results agree with DGLAP evolution, except at small ν, where the anomalous dimension saturates to a value that matches the BFKL anomalous dimension.

Energy correlators↗
DOE OSTI2023

Modeling, analysis, and optimization of complex nuclear processes and facilities via computational methods: The HALEU process case study

Improving and adapting industrial systems to timely meet changing programmatic and market demands is an important goal to achieve, including when operating and maintaining complex nuclear processes and facilities. However, changes to these complex systems are costly, particularly when they are already in place and bounded to stringent requirements and constraints such as when handling radioactive material and contaminated equipment. These conditions often exist when treating spent nuclear fuel remotely within shielded nuclear radiation chambers, commonly referred as hot cells, to condition nuclear material and/or fabricate products for utilization in other nuclear enterprises such as in the manufacture of advanced nuclear fuel. The illustrative case considered here is the production of high assay low enriched uranium (HALEU) products supporting the deployment of advanced nuclear reactors. For the HALEU program, resources invested were and are being systematically analyzed so that these investments are maximized in a facility that is nearly 60 years old. A methodology that has effectively enabled optimized and improvements in the Spent Fuel Treatment (SFT) program, and consequently the HALEU program, involves discrete event simulation as addressed in this article. Here, the quantification of multiple productivity metrics, including material processing rates, cycle times, bottlenecks, number of material transfers as well as equipment, workstation, and material handling utilization, has resulted in a myriad of diverse discoveries and data-informed decisions regarding process layout and constituent, labor levels and schedules, selection of new process units, storage needs, and other critical process configurations. This article describes such a computational capability being applied for decision-making, illustrates its application to an actual process and program, provides illustrative results, and argues how computational methods for the modeling, analysis, and optimization of complex processes and facilities does lead to informed decisions derived from data and not only from intuition.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Reducing ridesourcing empty vehicle travel with future travel demand prediction

Ridesourcing services provide alternative mobility options in several cities. Their market share has grown exponentially due to the convenience they provide. The use of such services may be associated with car-light or car-free lifestyles. However, there are growing concerns regarding their impact on urban transportation operations performance due to empty, unproductive miles driven without a passenger (commonly referred to as deadheading). This paper is motivated by the potential to reduce deadhead mileage of ridesourcing trips by providing drivers with information on future ridesourcing trip demand. Future demand information enables the driver to wait in place for the next rider’s request without cruising around and contributing to congestion. A machine learning model is employed to predict hourly and 10-minute future interval travel demand for ridesourcing at a given location. Using future demand information, we propose algorithms to (i) assign drivers to act on received demand information by waiting in place for the next rider, and (ii) match these drivers with riders to minimize deadheading distance. Real-world data from ridesourcing providers in Austin, TX (RideAustin) and Chengdu, China (DiDi Chuxing) are leveraged. Results show that this process achieves 68%–82% and 53%–60% reduction of trip-level deadheading miles for the RideAustin and DiDi Chuxing sample operations respectively, under the assumption of unconstrained availability of short-term parking. Deadheading savings increase slightly as the maximum tolerable waiting time for the driver increases. Further, it is observed that significant deadhead savings per trip are possible, even when a small percent of the ridesourcing driver pool is provided with future ridesourcing demand information.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Spectroscopic Investigation into P(NDI2OD-T2) Charge Localization

P(NDI2OD-T2), commonly referred to as N2200, stands out as a promising electron-transporting (n-type) polymer for low-cost, flexible (photo)electrochemical applications due to its reversible two-electron reduction and high electron mobility. UV–vis spectroelectrochemistry in the tetrabutyl ammonium hexafluorophosphate/acetonitrile electrolyte shows two sets of chemically reversible redox signals in the cyclic voltammetry corresponding to the reduction of the neutral polymer film to polaronic and bipolaronic species. These electrochemical signatures suggest a distinct electronic reorganization upon reduction (polaron/bipolaron formation), highlighting the need for molecular-level insights into how charges are accommodated within the polymer backbone. While it has been previously hypothesized that charge predominantly localizes on the naphthalene diimide (NDI) unit during reductive charging, specific changes in atomic environments that confirm this localization have not been characterized in n-type polymers. Herein, we use near-edge X-ray absorption fine structure (NEXAFS) spectroscopy to probe electronic transitions in an electrochemically charged polymer to deduce charge localization. The O K-edge (1s) spectra exhibit two distinct π* peaks; the intensity of the lower-energy π* a peak that corresponds to an excitation to a largely localized carbonyl state decreases with reductive potentials relative to the higher-energy π* b peak. We corroborate this with Raman spectroscopy at different potentials, which shows a decrease in intensity on the C–C/C═C and C═O stretching bands of NDI as well as a red shift of the carbonyl band due to the formation of a polaron on the NDI. Additionally, new Raman active NDI signals associated with elongated C═O and C═C bonds are observed at lower energy during the formation of charged states. Together with theoretical calculations, these findings show that the injected charge spatially localizes on the NDI units and is dominantly distributed on the carbonyl groups. In conclusion, the combination of NEXAFS, optical and vibrational spectroscopies, and theoretical calculations is generalizable to other pi-conjugated polymers and can identify charge localization for the further development of organic semiconductors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Colloidal Semiconductor Nanocrystal Lasers and Laser Diodes

Lasers and optical amplifiers based on solution-processable materials have been long-desired devices for their compatibility with virtually any substrate, scalability, and ease of integration with on-chip photonics and electronics. These devices have been pursued across a wide range of materials including polymers, small molecules, perovskites, and chemically prepared colloidal semiconductor nanocrystals, also commonly referred to as colloidal quantum dots. The latter materials are especially attractive for implementing optical-gain media as in addition to being compatible with inexpensive and easily scalable chemical techniques, they offer multiple advantages derived from a zero-dimensional character of their electronic states. These include a size-tunable emission wavelength, low optical gain thresholds, and weak sensitivity of lasing characteristics to variations in temperature. Here we review the status of colloidal nanocrystal lasing devices, most recent advances in this field, outstanding challenges, and the ongoing progress toward technological viable devices including colloidal quantum dot laser diodes.

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

Role of Solvent Rearrangement on Mg2+ Solvation Structures in Dimethoxyethane Solutions Using Multimodal NMR Analysis

One of the main impediments faced for predicting important emergent properties of a multivalent electrolyte (such as conductivity and electrochemical stability) is the lack of quantitative analysis of ion-ion and ion-solvent interactions, which manifest in solvation structures and dynamics. In particular, the role of ion-solvent interactions is still unclear in cases where the strong electric field from multivalent cations can influence structural evolution of lower permittivity organic solvent molecules on solvation structure. These influences are commonly refered to as electrostriction pheonmena. Using quantitative 1H, 19F, 17O, and 25Mg NMR together with 19F nuclear spin relaxation and diffusion measurments, we find an unusual correlation between ion concentration and solvation structure of Mg(TFSI)2 salt in dimethoxyethane (DME) solution. The domiant solvation structure evolves from contact ion pairs (i.e. [Mg(TFSI)(DME)1-2]+) to fully solvated clusters (i.e. [Mg(DME)3]2+) as salt concentration increases or as temperature decreases. This transition is coupled to a phase separation, which we study here between 0.06 M and 0.36 M. Subsequent analysis is based on an explanation of the electrostriction phenomena and the competion between solvent molecules and TFSI anions for cation coordination.

Chen, Ying↗
DOE OSTI2023

Stability Criteria for Self-Propagating Reaction Waves in Co/Al Multilayers

The propagation of self-sustained formation reactions in sputter-deposited Co/Al multilayers is known to exhibit a design-dependent instability. Multilayers having thin bilayers (<55 nm period) exhibit stable propagating waves, whereas those with a larger period react unstably. The specific two-dimensional (2D) instability observed involves the transverse propagation of a band in front of a stalled front commonly referred to as a “spin band.” Previous finite-element studies have shown that these instabilities are thermodynamically driven by the forward conduction of heat away from the flame front. However, the magnitude of that loss is inherently tied to the bilayer design in traditional bimetallic multilayers, which couples any proposed stability criteria to a varying critical diffusion distance. Here, this work utilizes a recently developed class of materials known as “inert-mediated reactive multilayers” to decouple the thermodynamic and kinetic contributions to propagating wave stability by reducing the stored chemical energy density in normally stable bilayer designs. By depositing an inert product phase (B2-CoAl) within the mid-plane of Co and Al reactant layers, spin instabilities arise as a function of both diluted volume and critical diffusion distance. From there, a stability criterion is determined for Co/Al multilayers based on enthalpy loss from the reaction zone, and its physical significance is explored.

36 MATERIALS SCIENCE↗