Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Processing”

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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Impact of different cleaning processes on the laser damage threshold of antireflection coatings for Z-Backlighter optics at Sandia National Laboratories

We have examined how different cleaning processes affect the laser-induced damage threshold of antireflection coatings for large dimension, Z-Backlighter laser optics at Sandia National Laboratories. Laser damage thresholds were measured after the coatings were created, and again 4 months later to determine which cleaning processes were most effective. There is a nearly twofold increase in laser-induced damage threshold between the antireflection coatings that were cleaned and those that were not cleaned. Aging of the coatings after 4 months resulted in even higher laser-induced damage thresholds. Also, the laser-induced damage threshold results revealed that every antireflection coating had a high defect density, despite the cleaning process used, which indicates that improvements to either the cleaning or deposition processes should provide even higher laser-induced damage thresholds.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Dehalogenation of electrochemical processing salt simulants with ammonium phosphates and immobilization of salt cations in an iron phosphate glass waste form

This study demonstrates the conversion of simulated pyroprocessing salt wastes [i.e., ER(SF) and ERV2] into chemically durable iron phosphate glass waste forms through reactions with ammonium hydrogen phosphate precursors [i.e., NH4H2PO4 and (NH4)2HPO4] and added Fe2O3. The reaction of the salt simulants with the phosphate precursors resulted in dehalogenation of the salt through the production of NH4Cl and NH4I (along with water), of which the NH4Cl can be used to produce UCl3 oxidant for use in the electrorefiner during pyroprocessing. These iron phosphate glasses contain a notably higher waste loading than the baseline glass-bonded sodalite ceramic waste form, which requires about 70 vol% sodalite to accommodate Cl from the salt, because they are dehalogenated prior to vitrification. The high waste loadings coupled with higher bulk densities (~3×103 kg/m3) than glass-bonded sodalite (~2.3×103 kg/m3) mean that these glasses have a higher storage volume, i.e., the volume required to immobilize a given mass of waste. The iron phosphate glass waste forms were characterized using a variety of techniques including physical property measurements and chemical durability testing. Following initial testing, a proof-of-concept demonstration was conducted to show that the NH4Cl generated from this process could be used to produce UCl3 using depleted uranium dendrites as a feedstock.

phosphate glass, pyroprocessing, waste forms, salt↗
DOE OSTI2015

A modular reactor design for in situ synchrotron x-ray investigation of atomic layer deposition processes

Synchrotron characterization techniques provide some of the most powerful tools for the study of film structure and chemistry. The brilliance and tunability of the Advanced Photon Source allow access to scattering and spectroscopic techniques unavailable with in-house laboratory setups and provide the opportunity to probe various atomic layer deposition (ALD) processes in situ starting at the very first deposition cycle. Here, we present the design and implementation of a portable ALD instrument which possesses a modular reactor scheme that enables simple experimental switchover between various beamlines and characterization techniques. As first examples, we present in situ results for (1) X-ray surface scattering and reflectivity measurements of epitaxial ZnO ALD on sapphire, (2) grazing-incidence small angle scattering of MnO nucleation on silicon, and (3) grazing-incidence X-ray absorption spectroscopy of nucleation-regime Er{sub 2}O{sub 3} ALD on amorphous ALD alumina and single crystalline sapphire.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Scanning ARM Cloud Radars. Part II: Data Quality Control and Processing

The Scanning ARM Cloud Radars (SACR’s) are the primary instruments for documenting the four-dimensional structure and evolution of clouds within a 20-30 km radius from the ARM fixed and mobile sites. Here, the post-processing of the calibrated SACR measurements is discussed. First, a feature mask algorithm that objectively determines the presence of significant radar returns is described. The feature mask algorithm is based on the statistical properties of radar receiver noise. It accounts for atmospheric emission and is applicable even for SACR profiles with few or no signal-free range gates. Using the nearest-in-time atmospheric sounding, the SACR radar reflectivities are corrected for gaseous attenuation (water vapor and oxygen) using a line-by-line absorption model. Despite having a high pulse repetition frequency, the SACR has a narrow Nyquist velocity limit and thus Doppler velocity folding is commonly observed. An unfolding algorithm that makes use of a first guess for the true Doppler velocity using horizontal wind measurements from the nearest sounding is described. The retrieval of the horizontal wind profile from the HS-RHI SACR scan observations and/or nearest sounding is described. The retrieved horizontal wind profile can be used to adaptively configure SACR scan strategies that depend on wind direction. Several remaining challenges are discussed, including the removal of insect and second-trip echoes. The described algorithms significantly enhance SACR data quality and constitute an important step towards the utilization of SACR measurements for cloud research.

climate↗
DOE OSTI2021

Processable High Electron Mobility {pi}-Copolymers via Mesoscale Backbone Conformational Ordering

The synthesis and experimental/theoretical characterization of a new series of electron-transporting copolymers based on the naphthalene bis(4,8-diamino-1,5-dicarboxyl)amide (NBA) building block are reported. Comonomers are designed to test the emergent effects of manipulating backbone torsional characteristics, and density functional theory (DFT) analysis reveals the key role of backbone conformation in optimizing electronic delocalization and transport. The NBA copolymer conformational and electronic properties are characterized using a broad array of molecular/macromolecular, thermal, optical, electrochemical, and charge transport techniques. All NBA copolymers exhibit strongly aggregated morphologies with significant nanoscale order. Copolymer charge transport properties are investigated in thin-film transistors and exhibit excellent electron mobilities ranging from 0.4 to 4.5 cm(2) V-1 s(-1). Importantly, the electron transport efficiency correlates with the film mesoscale order, which emerges from comonomer-dependent backbone planarity and extension. These results illuminate the key NBA building block structure-morphology-bulk property design relationships essential for processable, electronics-applicable high-performance polymeric semiconductors.

n‐↗
DOE OSTI2020

Description of the Fission Process: Nuclear Models for Fission Dynamics

Nuclear fission is the splitting of a heavy nucleus into two or more fragments, a process that releases a substantial amount of energy. It is ubiquitous in modern applications, critical for national security, energy generation and reactor safeguards. Fission also plays an important role in understanding the astrophysical formation of elements in the universe. Eighty years after the discovery of the fission process, its theoretical understanding from first principles remains a great challenge. In this paper, we present promising new approaches to make more accurate predictions of fission observables.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Modeling time-coincident ultrafast electron transfer and solvation processes at molecule-semiconductor interfaces

Kinetic models based on Fermi's Golden Rule are commonly employed to understand photoinduced electron transfer dynamics at molecule-semiconductor interfaces. Implicit in such second-order perturbative descriptions is the assumption that nuclear relaxation of the photoexcited electron donor is fast compared to electron injection into the semiconductor. This approximation breaks down in systems where electron transfer transitions occur on 100-fs time scale. Here, we present a fourth-order perturbative model that captures the interplay between time-coincident electron transfer and nuclear relaxation processes initiated by light absorption. The model consists of a fairly small number of parameters, which can be derived from standard spectroscopic measurements (e.g., linear absorbance, fluorescence) and/or first-principles electronic structure calculations. Insights provided by the model are illustrated for a two-level donor molecule coupled to both (i) a single acceptor level and (ii) a density of states (DOS) calculated for TiO{sub 2} using a first-principles electronic structure theory. These numerical calculations show that second-order kinetic theories fail to capture basic physical effects when the DOS exhibits narrow maxima near the energy of the molecular excited state. Overall, we conclude that the present fourth-order rate formula constitutes a rigorous and intuitive framework for understanding photoinduced electron transfer dynamics that occur on the 100-fs time scale.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Thermal Process Intensification: Transforming the Way Industry Uses Thermal Process Energy (Workshop Report)

The US Department of Energy’s (DOE’s) Advanced Manufacturing Office held the virtual workshop entitled “Thermal Process Intensification: Transforming the Way Industry Uses Thermal Process Energy” in November and December 2020. The workshop brought together participants from universities/laboratories, industries, equipment manufacturers, technology vendors, nongovernmental organizations, and subject-matter experts to discuss transformative technologies and strategies to substantially improve the performance (e.g., energy productivity, thermal efficiency, reduced greenhouse gas [GHG] emissions, reduced number of process steps) of thermal processing systems in the industrial sector. The US industrial sector accounts for 32% of the nation’s primary energy use (including feedstocks), and refining, chemicals, pulp and paper, iron and steel, and food products represent the top energy-consuming sectors. Thermal processing or process heating represents the largest energy use category; it accounts for 63% of all energy use in manufacturing. Additionally, thermal processing is the largest contributor of carbon dioxide (CO2) generation, resulting from combustion of fuels and process related chemical reactions, such as in the case of cement and lime production. The challenge of achieving net-zero industrial GHG emissions is colossal considering the established industrial base that depends mainly on carbon-based processes and energy sources; the time frame and cost to replace carbon-based energy sources and feedstocks; and the long-term outlook for development with large-scale adaptation of alternative non carbon–based technologies. The goals of the DOE Advanced Manufacturing Office Thermal Process Intensification Workshop were as follows: (1) Identify R&D gaps and opportunities to facilitate transformative improvement in industrial thermal processes beyond current technologies and allow for entirely new methods for processing materials; (2) Gain insight into new and innovative approaches to thermally intensify processes, reduce heat demand, harness waste heat, and use fuels and hydrocarbon feedstocks more efficiently; (3) Identify the R&D pathways to thermal process intensification (TPI) with the highest potential for impact and adoption by the industrial sector; (4) Define areas of research, development, and demonstration (RD&D) activities to accelerate development and application of emerging and transformative technologies to intensify thermal processes in industry. The scope and focus of the workshop were defined to meet these goals. Based on the available data for energy use and GHG emissions, the industries that collectively use more than 80% of the total process heating energy consumption were selected as primary focus areas. The chosen industries were combined into the following four groups based on similarities in their thermal processes: high-temperature metal processing (iron and steel industry, alumina-aluminum industry); high-temperature nonmetal and mineral processing (cement and glass industry); medium- to low-temperature thermal processing (food processing and pulp and paper industry as part of forest products sector); and hydrocarbon processing (petroleum refining and chemical industry). Furthermore, all potential TPI technologies associated with the processes defined were considered as part of the workshop. Different types of TPI technologies possible in industrial in the document.

42 ENGINEERING↗
DOE OSTI2022

A new multi-model absolute difference-based sensitivity (MMADS) analysis method to screen non-influential processes under process model and parametric uncertainty

Process-based models have been widely used for hydrologic modeling, and it is a common practice to use sensitivity analysis methods for excluding non-influential hydrologic processes from further investigation and/or model improvement. This study develops a new method called multi-model absolute difference-based sensitivity (MMADS) analysis method to screen non-influential system processes and parameters. MMADS is conceptually similar to the Morris method for addressing parametric uncertainty, but has a unique feature to address both process model uncertainty (i.e., a process may be represented by multiple process models) and process model parameter uncertainty (i.e., parameters associated with a process model are random). MMADS first evaluates absolute differences of a quantity of interest (i.e., a system model output) by varying process models and/or process model parameter values, and then calculates the mean and variance of the differences for investigating process influence. The mean measures overall influence of the process on the quantity of interest, and the variance estimates influence of nonlinear effects of the process and/or its interactions with other processes. MMADS is an extension of the Morris method from a parameter space to a joint parameter-model space for explicitly addressing both process model uncertainty and model parameter uncertainty. The performance of MMADS is evaluated by using two numerical experiments. One experiment is based on Sobol’s G*-function with ten product elements, and has analytical solutions of the MMADS mean and variance of absolute differences. The other experiment is for groundwater flow modeling which considers three processes (i.e., recharge, geology, and snowmelt) that interact with each other. Finally, results indicate that MMADS is computationally efficient and can identify non-influential processes of complex hydrological systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Water Governance Process Assessment: Evaluating the Link between Decision Making Processes and Outcomes in the Columbia River Basin

Academics and practitioners agree that in water governance, the quality of a decision making process should influence the quality of the outcome and the degree to which it is accepted by interested parties. However, finding a feasible way to evaluate and then improve the quality of a decision making process has proven elusive. Systematically collecting evidence of a link between process and outcome is also challenging. In my dissertation, I developed a synthesis framework for evaluating and improving water governance decision making to address these two challenges. The synthesis framework, which I call the Water Governance Process Assessment (Water GPA), draws upon 22 existing frameworks rooted in resilience, adaptive governance, and good governance. From these frameworks, I identified and provided a way to evaluate four characteristics critical to good water governance decision making processes: 1) accountability, 2) inclusivity, and 3) information, and 4) context. I applied the Water GPA framework to the recent reviews of the Columbia River Treaty by the United States and Canada. I collected data for the case studies through semi-structured interviews and surveys of process participants from the federal agencies, Tribal and First Nations, state/provincial governments, local governments, stakeholder interests, and citizens. I coded and analyzed the interviews using the qualitative analysis software QSR NVivo and the characteristics identified in the Water GPA framework. I used the two case study applications to demonstrate how to use the framework. I identified what aspects of the four process categories served as barriers and building blocks for good water governance in each water governance process. I also gleaned lessons learned and recommendations including some for determining process leadership, ensuring meaningful engagement and inclusivity, addressing sovereignty issues, setting decision criteria, sharing decision authority, allocating resources in future processes in the US and BC portions of the Columbia River Basin and similar basins. In my case studies, I also investigated which characteristics of the water governance decision making process influenced the direct outcomes of those processes (the decisions) as well as other non-target outcomes (such as trust, co-produced science, new coalitions, etc.). All four characteristics outlined in the Water Governance Process Assessment (Water GPA), played some role in the development of the content and/or support of the two case study decision documents (US Regional Recommendation and BC Provincial Decision). Generally, when the characteristic of the process was done well, it improved the legitimacy and acceptance of the decision. At the same time performing poorly in one area did not necessarily torpedo the process or decision. In both case studies, it appears that the interplay between the process characteristics (that is where two or more characteristics converge) had a greater influence over the decision. Further work is needed to clearly identify what characteristics of a process are most influential in different situations. The Water GPA is one useful tool for this effort.

13 HYDRO ENERGY↗
DOE OSTI2020

Lightweight Software Process Improvement Using Productivity and Sustainability Improvement Planning (PSIP)

Productivity and Sustainability Improvement Planning (PSIP) is a lightweight, iterative workflow that allows software development teams to identify development bottlenecks and track progress to overcome them. In this paper, we present an overview of PSIP and how it compares to other software process improvement (SPI) methodologies, and provide two case studies that describe how the use of PSIP led to successful improvements in team effectiveness and efficiency.

Heroux, Michael A.↗