Integrating Thermal Tools Into the Mechanical Design Process
The intent of mechanical design is to deliver a hardware product that meets or exceeds customer expectations, while reducing cycle time and cost.
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The intent of mechanical design is to deliver a hardware product that meets or exceeds customer expectations, while reducing cycle time and cost.
Images processed rapidly in rugged, compact device. Conceptual integrated optical image processor performs complicated analog calculations, including Fourier transforms, convolutions, correlations, and matrix multiplications. Compact and rugged on account of monolithic structure, processor faster than equivalent all-electronic devices because calculations require only time for light to travel across device; processing speed limited by electronic input and output circuits.
The concept of sustainability inherently spans multiple spatial scales, sectors, variables, and time horizons. This study links a recently developed method of assessing present-day agricultural sustainability across environmental, economic, and social dimensions with a process-based integrated assessment model, in order to allow forward-looking analysis of sustainability by region and scenario. The sustainable agriculture matrix estimates present-day agricultural sustainability at the national level using 18 indicator variables, of which this study estimates nine to the year 2100, using an enhanced version of the Global Change Analysis Model. Scenarios include a reference scenario, and scenarios that apply the following measures, both individually and in combination, that are thought to improve sustainability: yield intensification, transition toward more plant-based (“flexitarian”) diets, and economy-wide greenhouse gas emissions mitigation. The scenarios illustrate considerable complexity and tradeoffs inherent to efforts to improve agricultural sustainability in all regions globally. For example, yield intensification typically increases nitrogen pollution, flexitarian diets can reduce agricultural output, and greenhouse gas mitigation efforts may either increase deforestation or crowd out crop and livestock production due to consequent bioenergy demands. However, there is considerable inter-regional heterogeneity in the responses, and the importance of such secondary responses also differs by region. The analysis and post-processing methods developed in this study allow quantification and visualization of the absolute and relative magnitude of the tradeoffs between agricultural sustainability indicator variables across regions, time periods, and scenarios.
The Mars 2020 Perseverance Rover was launched on July 30th, 2020 with one of the most complex robotic systems ever implemented on an interplanetary mission. Much of this robotic complexity resides in the Rover Sampling and Caching Subsystem (SCS) to enable collection of Martian samples for eventual return to earth and preparation of surfaces for close-up surface science observations. Two robotic arms are used by SCS: the large Robotic Arm (RA) positions the coring drill and science instruments mounted to the Turret for surface interactions, and the smaller Sample Handling Assembly (SHA) manipulates Sample Tube Assemblies (STA) within the Adaptive Caching Assembly (ACA) to prepare them for sample collection, processing, and hermetic sealing. The robotic arms interact with the Martian surface and other SCS components in many ways and in a variety of configurations, with positioning accuracy requirements ranging from tens of millimeters for some surface interactions down to sub-millimeter accuracy for some ACA interactions.This paper describes the process and tool used to calculate the SCS robotic interaction positioning budgets and verify the as-built hardware when delivered. To ensure that these robotic systems are able to perform their tasks, each robotic interaction with another element was broken down into its composite functions. To calculate a positioning budget margin for each function, an allowable was defined and then compared to the list of error sources that contribute to misalignment. Across the subsystem, over 250 functions were identified to be assessed, with almost 500 error sources feeding into their budget calculations. In addition to using as-built values in the budgets for SCS Verification and Validation (V&V) after the hardware was complete, these budgets were populated with design data during the design phase to identify areas of concern and guide hardware design to ensure positive position budget margins.Because of the size of the SCS team that had inputs to the positioning budgets and the sheer number of items in the budgets that needed to be created, updated, and verified, having a tool that would allow for simultaneous access and robust data integrity and processing was imperative. To accomplish this, a web-based MySQL database was created that allowed users to create function position budgets, link individual errors and allowables to them, and view function position budget margin reports. Each error and allowable records data for lateral, normal, angular, and clocking errors, with the ability to add as-built data for up to four different hardware builds. Margin reports can be generated for either design values alone or replacing design data with as-built data when available. These as-built reports are used for final verification of the SCS positioning requirements. Ultimately, the SCS positioning budget process and database tool led to successful interactions during test and an SCS robotic system that is ready to perform sample acquisition and caching on the surface of Mars.
This project addresses the needs of the U.S. Department of Energy (DOE) to develop advanced monitoring technologies and protocols to track the fate of subsurface carbon dioxide (CO2) plumes for carbon storage. Specifically, the project seeks to develop and test a unique and novel system of technologies consisting of electromagnetic data acquisition, coupled multiphysics imaging, and reservoir model enhancement to understand the migration and long-term distribution of CO2 in the subsurface. The overarching objective is to develop an integrated approach for long term monitoring of carbon storage. The two main components of the project include the methodology development and the test of the method at a field site. The methodology component consists of 1) developing the field procedure and protocol for collecting time-lapse controlled-source electromagnetic (CSEM) data with source electric current injected into the subsurface through wellbore casings; 2) building of background 3D electrical conductivity utilizing multiple sources of data such as supplemental surface transient EM (TEM) surveys, well-logs, and seismic structural information, for enhancing CSEM signal from reservoir depths; and 3) coupled multiphysics simulations and inversion of CSEM data constrained by production data and by structural information from seismic imaging of the reservoir and overlying formations. The testing component used the field site of Bell Creek Oil Field, which served both as a field laboratory for the method development as well as a test site to evaluate the CSEM signal strengths and the methodology developed in this research project. We have accomplished all the proposed tasks and developed the methodology as planned. These include the procedure for time-lapse CSEM data acquisition, data processing techniques, integration with 3D conductivity model building, fast reservoir simulation for history matching using machine learning, and interpreting CSEM data with coupling to the reservoir modeling. Collectively, the outcome of these tasks form a coherent workflow that can be applied to monitor dedicated carbon storage in saline reservoirs. The testing component evaluated the applicability and limitations of the method, and concluded that the method would be ideal for monitoring dedicated carbon storage sites utilizing saline reservoirs.
Advanced nuclear reactors offer a new set of features to energy generation, due to their ability to adapt to variable energy demand, operate autonomously, be deployed in rural locations and monitored remotely, afford compact size and lower power ratings, and rely on novel technologies to achieve safer operations. Thus, a requirement for the success of these reactors is the use of intelligent forms of control to track changing power demands, make autonomous decisions, and reduce the need for human involvement. Regulatory requirements pertaining to control of nuclear reactors could be met via historical means of control; however, these are not expected to enable the level of highly autonomous operations desired in advanced nuclear reactors. Historical control methods rely on both logical and high-performance (HP) control. These two types of control are usually used separately, with a human element being introduced whenever decisions are cascaded from one science to another. AI/ML control, on the other hand, can replace the human element in the current U.S. fleet of nuclear power plants (NPPs) by acting as a supervisory optimizer that understands the plant internal/external variables in order to make control decisions, and can easily handle non-linear and multi-input/multi out (MIMO) decisions—another requirement for advanced nuclear reactors that could be difficult to handle via logical and HP control. Because of the harsh operating environments produced in advanced reactors, resulting in the frequent failure of sensors and other types of equipment, and considering the lack of operating history for advanced nuclear reactors, control of advanced nuclear reactors would necessitate relying on a model that can track and adapt to the actual process (i.e., a digital twin). This digital twin can make approximations when knowledge and data are unavailable and would evolve as more knowledge is gained. The reactor control must also be risk-informed to account for the high-consequence nature of advanced reactors. This report introduces a high-level (i.e., not method- or process-specific) integration of the three different control and digital twinning methods able to meet the requirements for advanced nuclear reactors. These methods could be applied during both the operational and design stages of these reactors. The aim is to demonstrate how each method interfaces with and highlights enabling solutions necessitated by the unique features of advanced nuclear reactors.
Naturally occurring organic materials containing humic acids show a strong affinity towards rare earth elements (REE) and other critical elements. Leaching experiments on lignite coal waste produced from construction sand production revealed that the contained REEs were associated with the organic matter. Furthermore, adsorption studies revealed that the lignite waste was capable of extracting REEs from a model solution and increased the REE content of the lignite waste by more than 100%. As such, this study aimed to utilize the lignite waste to adsorb REEs from pregnant leach solutions and acid mine drainage sources having low REE concentrations and subsequently leach the lignite material to produce pregnant leach solutions containing relatively high amounts of REEs, which benefits the performance and economic viability of downstream separation and purification processes. An integrated flowsheet was developed based on this concept and tested at a pilot scale. The pregnant leachate solution (PLS) was generated from a heap leach pad containing 2000 tons of Baker seam coarse refuse. The pilot scale circuit was comprised of aluminum precipitation, adsorption using the waste lignite, and rare earth-critical metal (RE-CM) precipitation stages in succession. The results indicated that the aluminum precipitation stage removed over 88% and 99% of the Al and Fe, respectively. The adsorption stage increased the REE content associated with the waste lignite from 457 ppm to 1065 ppm on a whole mass basis. Furthermore, the heavy REE (HREE) content in the feedstock increased by approximately 250%, which raised the percentage of HREE in the REE distribution by 19 absolute percentage points. In addition to the REEs, concentrations of other critical elements such as Mn, Ni, and Zn also improved by 75%, 37%, and 250%, respectively. Bench-scale tests revealed that increasing the solids concentration in the waste lignite and PLS mix from 1% to 20% by weight enhanced the adsorption efficiency from 32.0% to 99.5%, respectively. As such, a new flowsheet was proposed which provides significantly higher REE concentrations in the PLS that can be fed directly to solvent extraction and/or oxalic acid precipitation and, thereby, enhancing process efficiency and economics.
Forest Service studies for integrating remotely sensed data into existing information systems highlight a need to: (1) re-examine present methods of collecting and organizing data, (2) develop an integrated information system for rapidly processing and interpreting data, (3) apply existing technological tools in new ways, and (4) provide accurate and timely information for making right management decisions. The Forest Service developed an integrated information system using remote sensors, microdensitometers, computer hardware and software, and interactive accessories. Their efforts substantially reduce the time it takes for collecting and processing data.
A technique based on accelerating positive nitrogen ions onto an aluminum layer has been demonstrated to be effective in forming thin (<2 nm thick) layers of aluminum nitride (AlN(x)) for use as tunnel barriers in Nb/Al-AlN(x)/Nb superconductor/insulator/ superconductor (SIS) Josephson junctions. AlN(x) is the present material of choice for tunnel barriers because, to a degree greater than that of any other suitable material, it offers the required combination of low leakage current at high current density and greater thermal stability. While ultra-thin AlN films with good thickness and stoichiometry control are easily formed using techniques such as reactive molecular beam epitaxy and chemical vapor deposition, growth temperatures of 900 C are necessary for the dissociative adsorption of nitrogen from either nitrogen (N2) or ammonia (NH3). These growth temperatures are prohibitively high for the formation of tunnel barriers on Nb films because interfacial reactions at temperatures as low as 200 to 300 C degrade device properties. Heretofore, deposition by reactive sputtering and nitridation of thin Al layers with DC and RF nitrogen plasmas have been successfully used to form AlN barriers in SIS junctions. However, precise control over critical current density Jc has proven to be a challenge, as is attaining adequate process reproducibility from system to system. The present ion-beam technique is an alternative to the plasma or reactive sputtering techniques as it provides a highly controlled arrival of reactive species, independent of the electrical conditions of the substrate or vacuum chamber. Independent and accurate control of parameters such as ion energy, flux, species, and direction promises more precise control of film characteristics such as stoichiometry and thickness than is the case with typical plasma processes. In particular, the background pressure during ion-beam nitride growth is 2 or 3 orders of magnitude lower, minimizing the formation of compounds with contaminants, which is critical in devices the performance of which is dictated by interfacial characteristics. In addition, the flux of incoming species can be measured in situ using ion probes so that the dose can be controlled accurately. The apparatus used in the present ion-beam technique includes a vacuum chamber containing a commercial collimated- ion-beam source, a supply of nitrogen and argon, and an ion probe for measuring the ion dose. Either argon or nitrogen can be used as the feed gases for the ion source, depending on whether cleaning of the substrate or growth of the nitride, respectively, is desired. Once the Nb base electrode and Al proximity layer have been deposited, the N2 gas line to the ion beam is vented and purged, and the ion-source is turned on until a stable discharge is obtained. The substrate is moved over the ion-beam source to expose the Al surface layer to the ion beam (see figure) for a specified duration for the formation of the nitride tunnel barrier. Next, the Nb counter-electrode layer is deposited on the nitride surface layer. The Nb/Al- AlN(x)/Nb-trilayer-covered substrate is then patterned into individual devices by use of conventional integrated-circuit processing techniques.
Forest lands cover the globe and are important sources for providing ecosystem services including: carbon sequestration, biodiversity, timber, air and water quality. As such, counties around the world have dedicated programs for managing them. Accurate and timely information concerning the status of these forests (moisture, biomass, disturbance type, etc.) is essential to those Nations’ human and ecological health as well as economy. The joint NASA/US Forest Service workshop focused on arming forest land managers with observations and remote sensing information from the upcoming NASA-ISRO (Indian Space Research Organization) SAR (Synthetic Aperture Radar) (NISAR) satellite mission (expected to launch early 2022). Participants included representatives from different US Federal Agencies, private sector, and non-governmental organizations (NGO) that are key players in facilitating integration of Earth Observations (EO) into forest management and decision support workflows. They included scientists, technicians, and program managers with a responsibility for data acquisition and exploitation such as product development, delivery, and use, and capacity building. Discussions were held over two days to convey the broader forest and disturbance community information needs for various representative participants and programs and to facilitate the delivery of NISAR mission geospatial products and observational capabilities. Case studies were presented to demonstrate the current state of practice in the use of SAR remote sensing for applications of direct importance to forest and disturbance land management community. Eleven organizations presented their information requirements in response to a set of questions provided by the NASA team, then the NASA team responded by describing the degree to which NISAR could meet these requirements. Discussion ensued about needed data product specifications to increase utility (e.g., projection, latency, etc.), tools and capacity building. The general findings of this workshop were that (a) NISAR observations will be particularly useful to the global forest carbon and disturbance monitoring applications, but that certain data product design decisions (projections and radiometric and terrain corrections) need to be considered to increase utility; b) the biomass and disturbance detection algorithms meet many of the community needs, however there are other information products of value (e.g., soil moisture or disturbance classification, not just detection) and all products should be compliant with existing community standards for reporting uncertainty; c) providing SAR education to the community will be key specifically thinking about putting the information first and the SAR theory second, providing a simple guide of standard data processing steps (e.g., dB (decibel) to power conversion and speckle filtering); d) the community needs a user-friendly interface for finding free, archived data over their geographic regions of interest; e) user-friendly tools that connect to open-sources GIS (Global Information System) software (e.g., QGIS (Quantum GIS)) that include a graphical user interface (GUI) for SAR processing that enables both download and cloud processing. To integrate these findings and prepare the community before NISAR launches, it was suggested that there be a dedicated NISAR Forest and Disturbance Applications Working Group (as per the specifications in the NISAR Utilization Plan). After launch, it was decided that the community continue capacity building activities.
Captured carbon dioxide (CO 2 ) streams contain impurities that must be removed to meet specifications for safe transport, storage, and utilization. Among these impurities, oxygen poses challenges due to its high reactivity and potential to cause corrosion, motivating stringent purity limits below 10 ppmv. Building on recent experimental demonstrations of catalytic oxygen removal using hydrogen (H 2 ), carbon monoxide (CO), methanol (CH 3 OH), and methane (CH 4 ) as reducing agents, this study presents a technoeconomic (TEA) and life cycle assessment (LCA) of these four catalytic purification pathways. Process flowsheets were developed and simulated in Aspen Plus for CO 2 streams representative of both low-temperature and high-temperature capture processes, with integrated heat recovery and energy optimization. Results showed that total purification costs were dominated by feedstock procurement and electricity consumption. Among the studied reducing agents, the CH 4 -assisted route achieved the lowest purification cost and highest CO 2 recovery. Sensitivity analyses showed that the H 2 route became competitive at H 2 prices below $\$$0.56/kg to $\$$0.84/kg, depending on the CO 2 feed temperature conditions. In conclusion, environmental impacts were primarily driven by indirect CO 2 emissions from raw material production and utility consumption.
The pharmaceutical industry continuously looks for ways to improve its development and manufacturing efficiency. In recent years, such efforts have been driven by the transition from batch to continuous manufacturing and digitalization in process development. To facilitate this transition, integrated data management and informatics tools need to be developed and implemented within the framework of Industry 4.0 technology. Here, in this regard, the work aims to guide the data integration development of continuous pharmaceutical manufacturing processes under the Industry 4.0 framework, improving digital maturity and enabling the development of digital twins. This paper demonstrates two instances where a data integration framework has been successfully employed in academic continuous pharmaceutical manufacturing pilot plants. Details of the integration structure and information flows are comprehensively showcased. Approaches to mitigate concerns in incorporating complex data streams, including integrating multiple process analytical technology tools and legacy equipment, connecting cloud data and simulation models, and safeguarding cyber-physical security, are discussed. Critical challenges and opportunities for practical considerations are highlighted.
Process intensification and integration for sustainable design play an essential role in addressing and alleviating severe sustainable development challenges. It is prudent to evaluate a process design in its early stage development to ensure the process can achieve sustainability goals. The primary goal of a sustainability evaluation is to assess the impact of systems on areas sought to be protected and maintained over time, such as human well-being and ecosystems (Schaubroeck, T. and Rugani, B. (2017). A revision of what life cycle sustainability assessment should entail: towards modeling the net impact on human well-being. Journal of Industrial Ecology 21 (6): 1464-1477). Parenthetically, sustainable process design to convert biomass to fuels and chemicals plays an integral part in the bioeconomy sustainability. It is recognized that the integration of sustainability in process design is core to the mission in developing renewable fuels and should be considered a necessary practice in biorefinery design. This study demonstrates the use of Gauging Reaction Effectiveness for ENvironmental Sustainability of Chemistries with a multi-Objective Process Evaluator (GREENSCOPE) as a tool to help track progress on process sustainability performance attributed to conversion improvement. With the incorporation of a wide range of indicators, GREENSCOPE captures the multi-dimensional aspect of the process design and operation. As opposed to conventional techno-economic analysis and life cycle assessment (in which the focuses are limited to economic and environmental aspects), GREENSCOPE enables the consideration of process intensification and integration for sustainable design. A high-octane gasoline production from woody biomass feedstock is used as a case study to demonstrate the approach.
Produced water (PW) generated from hydraulic fracturing operations was treated using an integrated electrocoagulation, ultrafiltration, membrane distillation, and crystallization process (EC UF MDC). The aim was to determine the viability of this integrated process for maximizing water recovery. The results obtained here indicate that optimizing the various unit operations could lead to increased recovery of PW. Membrane fouling limits all membrane separation processes. A pretreatment step to suppress fouling is essential. Here, removal of total suspended solids (TSS) and total organic carbon (TOC) was achieved by electrocoagulation (EC) followed by ultrafiltration (UF). The hydrophobic membrane used in membrane distillation may be fouled by dissolved organic compounds. Reducing membrane fouling is essential to increase the long-term durability of the membrane distillation (MD) system. In addition, combining membrane distillation with crystallization (MDC) can help reduce scale formation. By inducing crystallization in the feed tank, scale formation on the MD membrane was suppressed. The integrated EC UF MDC process can impact Water Resources/Oil & Gas Companies. Conservation of surface and groundwater is possible by treating and reusing PW. Additionally, treating PW reduces the amount of PW disposed in Class II disposal wells and promotes more environmentally sustainable operations.
Electromagnetic (EM) fields can trigger a range of surprising responses in materials. Microwave radiation (MWR), a type of EM field in the frequency range of 0.3–300GHz, can lower the synthesis temperature required for ceramics such as TiO2 and induces mixed amorphous–crystalline phase compositions. To better understand the effects of MWR on matter, structural changes during microwave heating and MWR-assisted synthesis using in situ synchrotron X-ray diffraction are studied. Anisotropic expansion–contraction of lattice parameters under microwave-radiation is observed, which contradicts the results from conventional thermal heating. When as-received TiO2 powders are heated with MWR, an instantaneous decrease in the intensities of diffraction peaks indicates decrystallization/amorphization. High resolution electron microscopy supports these observations. Raman spectroscopy and X-ray photoemission spectroscopy indicate increased defect-generation under microwave exposure. Molecular dynamics simulations on the anatase phase of TiO2 suggests that introducing an oxygen vacancy can lead to the formation of an interstitial–vacancy pair resulting in anisotropic expansion–contraction of the lattice. These unique responses of ceramics under externally applied fields provide direct evidence for nonthermal coupling between EM fields and matter. Understanding such nonthermal, field-driven processes has implications in engineering low-temperature processes for integrating ceramics with polymers for flexible electronics, energy harnessing, and storage applications.
Hafnia-based ferroelectrics hold promise to reduce energy demand for computing by enabling compute-in-memory and as non-volatile memories. The ferroelectric phase in this material system is, in part, stabilized by oxygen vacancies. While oxygen vacancies may be a necessity for phase stability, they limit device endurance through diffusion and accumulation into conducting channels. Herein, it is shown that oxygen diffusion is spatially variable within individual grains of ferroelectric hafnium zirconium oxide (HZO). Using 18 O tracers and finite difference modeling, it is shown that grain boundaries and regions near electrode interfaces allow for relatively rapid oxygen diffusion, with values as much as 10 4 larger than the grain cores. Further, the selection of electrode material affects the diffusion coefficients across all microstructural regions. HZO films in contact with TiN electrodes result in more oxygen-deficient HZO films and higher oxygen diffusion coefficients. Tungsten electrodes result in fewer vacancies and lower diffusion coefficients. Diffusion activation energy differences between the HZO with the two electrodes is reconciled by differing populations of charged and uncharged oxygen vacancies. This insight into the local vacancy populations and diffusion pathways provides a platform for designing hafnia-based films, deposition processes, and integration strategies to reduce vacancy gradients and improve performance.
Formamidinium (FA)-based lead iodide perovskites have emerged as the most promising light-absorber materials in the prevailing perovskite solar cells (PSCs). However, they suffer from the phase-instability issue in the ambient atmosphere, which is holding back the realization of the full potential of FA-based PSCs in the context of high efficiency and stability. Herein, the tetraethylorthosilicate hydrolysis process is integrated with the solution crystallization of FA-based perovskites, forming a new film structure with individual perovskite grains encapsulated by amorphous silica layers that are in situ formed at the nanoscale. The silica not only protects perovskite grains from the degradation but also enhances the charge-carrier dynamics of perovskite films. The underlying mechanism is discussed using a joint experiment-theory approach. Through this in situ grain encapsulation method, PSCs show an efficiency close to 20% with an impressive 97% retention after 1000-h storage under ambient conditions.
Abstract The unique capability of 3D printing to create geometric complex structures presents a promising avenue for producing 3D electrodes aimed at enhancing power and energy densities within constrained spaces, which is challenging to achieve through traditional slurry casting methods. However, despite advancements over the years, 3D‐printed batteries have faced limitations in terms of mechanical robustness to endure significant volume changes during cycling and restricted electrochemical performance due to the lack of adequate electrode feedstock development or post‐processing treatments. Herein, a high‐loaded electrode filament with ≈65 wt.% fillers, enabling the fabrication of structural electrodes with improved electrochemical performance and superior mechanical properties, is developed. Through a combination of 3D printing and post‐processing techniques, interdigitated structures with high areal‐loading density, resulting in a full cell with an enhanced areal capacity of ≈12.28 mAh cm −2 at ≈0.92 mA cm −2 is fabricated. Moreover, the structural batteries, treated through the carbonizing process, are integrated by the carbon coating generated during carbonization, exhibiting remarkable compressive properties (with a modulus of 18.5 MPa and a strength of 1.09 MPa). Overall, the findings demonstrate the promising potential of 3D printed batteries for practical applications, while showcasing the scalability and design flexibility offered by 3D printing technology.