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At least 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

DOE Bioenergy Technologies Office (BETO) 2023 Project Peer Review: WBS 2.4.1.100 Bench Scale Research & Development

Bench Scale Integration develops and optimizes fermentation processes to produce bio-based fuels and chemicals for commercial scale-up. The project uses fermentation science to achieve high titers and production rates by, for example, manipulating how the microorganisms are fed biomass sugars and nutrients, modifying fermentation conditions (pH, temperature, aeration) or developing online control strategies for better fermentation operations and high titer, rates, and yield (TRY). For this period of performance, we continued our development of a commercial-ready 2,3-butanediol (BDO) fermentation from biomass sugars utilizing NREL's proprietary Zymomonas mobilis microorganism. The engineered Z. mobilis can use all the main sugars in corn stover biomass, which are glucose, xylose, and arabinose. BDO is a versatile, low-carbon chemical which can be catalytically upgraded to a variety of hydrocarbon fuels and chemicals. The project had three goals during this review period; evaluate the technical feasibility of using whole slurry pretreated corn stover to achieve the techno-economic analysis (TEA) performance goals, continue optimizing a liquor-based fed-batch fermentation process for high titer, and develop strategies to enable scale-up. After evaluating different iterations of a whole slurry fermentation that did not meet the TEA goals, a Go/No-Go decision was made to pivot to liquor-only with new TEA performance targets, the main one being 140 g/L titer. We successfully met this goal, producing 141 g/L BDO at 1 g/L-hr productivity and 84% process yield. This titer and productivity attracted industrial interest to scale the fermentation resulting in a Technology Commercialization Fund project award in 2022. We used an NREL developed near-infra red (NIR) spectroscopy method for rapid analysis which allowed for changes to aeration levels and sugar feeding during the fermentation to maximize BDO production. The NIR analysis can be done using a hand-held spectrometer, essentially taking the analysis on to the plant floor during scale-up and preliminary work shows the feasibility of using an online probe for continuous monitoring and control. The other scale-up tool is mapping oxygen transfer coefficient (kLa) and oxygen transfer rate (OTR) in various vessels to find conditions that match the optimized 500 mL vessels. Showing a correlation to the mapping work, which is done with water and a dissolved oxygen probe, can reduce the risk of failed fermentations during scale-up. Our end-of-project goal is to meet the design target BDO titer (140-150 g/L) from DMR corn stover liquor at 1000L or larger scale to demonstrate BDO process design case and transfer the technology to industrial fermentation stakeholders for commercialization.

2 3-butanediol↗
NASA NTRSDate not supplied

Automated Multi-Robot Assembly of Compliance Optimized Structures

Autonomous assembly of large structures is one of the fundamental challenges on the way towards NASA’s objectives of deep space exploration. In this work, we propose an algorithmic framework to optimize the assembly process of a prescribed target structure by constraining the assembly effort as well as maintaining structural soundness throughout the process. This framework uses structural topology optimization with assembly effort metrics to generate checkpoints for robotic traversal algorithms. Assembly effort is quantified by the Wasserstein metric between consecutive structural configurations during the assembly process. The robotic assembly task is split into two subtasks, where we first optimize for a set of key frames, then perform reconfiguration between consecutive frames. Key frames are optimized by adopting topology optimization techniques to reduce assembly effort and maintain structural integrity during the assembly process, while reconfiguration between key frames is performed using a path planning algorithm with a minimum weight maximum matching approach on a bipartite graph. We employ a Crystalline robot model in which each structural element is capable of locomotion through the structure and locking into place with neighboring elements after reaching its destination. An example assembly of a two-dimensional cantilever beam under volume constraints and structural compliance considerations is presented to demonstrate the approach. Finally, we conclude by discussing possible future extensions to this work, including adoption of better metrics, extension to three-dimensional large-scale problems, and exacting finer control of structural integrity during the path-planning phase.

robotic assembly↗
DOE OSTI2022

Optimization of metal-supported solid oxide fuel cells with a focus on mass transport

Performance of symmetric-architecture metal-supported solid oxide fuel cells was improved significantly by optimizing the catalyst infiltration process and metal support structure. Optimization of component structure and processing parameters was performed during tape-casting and fabrication of button cells. Mass transport of oxygen in the metal support was identified as a major limitation. To overcome this limitation, pore former loading and thickness of the metal support (130–250 μm) were optimized. The catalyst infiltration process was also improved by studying the impact of firing temperature (400 °C–900 °C) and infiltration cycle numbers (1–15). The maximum power density of the optimized cell was 0.9 W cm –2 at 700°C using hydrogen as a fuel, a three-fold increase over the baseline cell performance. The degradation rate of optimized cells at 550 °C, 600 °C, and 700 °C was 2%, 4.5%, and 5.5% per 100 h, respectively. Here, the phenomena of mass transport, catalyst coarsening, and chromium poisoning on the catalyst were analyzed by electrochemical impedance spectroscopy and scanning electron microscopy.

13 HYDRO ENERGY↗
NASA NTRS1981

A Module Experimental Process System Development Unit (MEPSDU)

The purpose of this program is to demonstrate the technical readiness of a cost effective process sequence that has the potential for the production of flat plate photovoltaic modules which met the price goal in 1986 of $.70 or less per watt peak. Program efforts included: preliminary design review, preliminary cell fabrication using the proposed process sequence, verification of sandblasting back cleanup, study of resist parameters, evaluation of pull strength of the proposed metallization, measurement of contact resistance of Electroless Ni contacts, optimization of process parameter, design of the MEPSDU module, identification and testing of insulator tapes, development of a lamination process sequence, identification, discussions, demonstrations and visits with candidate equipment vendors, evaluation of proposals for tabbing and stringing machine.

Source record↗
NASA NTRS1993

Processing parameters associated with scale-up of balloon film production

A method is set forth for assessing strain-rate profiles that can be used to develop a scale-up theory for blown-film extrusion. Strain rates are evaluated by placing four ink dots on the stalk of an extruded bubble to follow the displacements of the dots as a function of time. The instantaneous Hencky strain is obtained with the displacement data and plotted for analysis. Specific attention is given to potential sources of error in the distance measurements and corrections for these complex bubble geometries. The method is shown to be effective for deriving strain-rate data related to different processing parameters for the production of balloon film. The strain rates can be compared to frostline height, blow-up ratio, and take-up ratio to optimize these processing variables.

Simpson, D. M.↗
NASA NTRS2014

Wing Configuration Impact on Design Optimums for a Subsonic Passenger Transport

This study sought to compare four aircraft wing configurations at a conceptual level using a multi-disciplinary optimization (MDO) process. The MDO framework used was created by Georgia Institute of Technology and Virginia Polytechnic Institute and State University. They created a multi-disciplinary design and optimization environment that could capture the unique features of the truss-braced wing (TBW) configuration. The four wing configurations selected for the study were a low wing cantilever installation, a high wing cantilever, a strut-braced wing, and a single jury TBW. The mission that was used for this study was a 160 passenger transport aircraft with a design range of 2,875 nautical miles at the design payload, flown at a cruise Mach number of 0.78. This paper includes discussion and optimization results for multiple design objectives. Five design objectives were chosen to illustrate the impact of selected objective on the optimization result: minimum takeoff gross weight (TOGW), minimum operating empty weight, minimum block fuel weight, maximum start of cruise lift-to-drag ratio, and minimum start of cruise drag coefficient. The results show that the design objective selected will impact the characteristics of the optimized aircraft. Although minimum life cycle cost was not one of the objectives, TOGW is often used as a proxy for life cycle cost. The low wing cantilever had the lowest TOGW followed by the strut-braced wing.

Wells, Douglas P.↗
DOE OSTI2023

Development of process parameters and post-build conditions for qualification of LPBF 316 SS

To harness the potential of laser powder bed fusion (LPBF) 316H stainless steel (SS) for use in advanced nuclear reactors, extensive research efforts are needed to develop optimal laser processing parameters and appropriate heat treatments, taking into account various manufacturing platforms and locations. Furthermore, it is crucial to assess the material properties in environments relevant to reactor operating conditions. In collaboration with Oak Ridge National Laboratory (ORNL) and Los Alamos National Laboratory (LANL), Argonne National Laboratory (ANL) is dedicated to gaining insights into how the manufacturing process and post-build treatments impact the performance of LPBF 316H SS. This report provides an overview of ANL's research findings for FY23, focusing on LPBF 316H SS produced using a Renishaw AM400 laser system. Specifically, our research has concentrated on three key areas: 1) Optimum laser processing parameters: Leveraging the high-throughput printing technology, we systematically varied the laser power, exposure time and point distance within the same build. By measuring the as-printed porosity, we identified an optimum printing parameter window that produced materials with near-complete density; 2) Post-built treatment development: Materials printed with the optimum laser parameters underwent treatments including stress relief, solution annealing, and hot isostatic pressing. Subsequently, we fabricated tension, creep, and fatigue specimens from materials subjected to these different conditions. Over the next year, a series of scoping tests will be conducted to facilitate the selection of the most suitable post-build treatment condition; 3) Thermal aging effects on microstructure and properties: thermal aging at 550°C, 650°C and 750°C was conducted on LPBF 316H SS specimens up to 2500 h. Microstructural characterization was performed with electron microscopy, and the evolution of the dislocation cell structures and secondary phases was studied. Microhardness tests and tension tests were conducted to quantify changes in mechanical properties. The results revealed that the aged LPBF 316H SS exhibited a high density of Cr-rich and Mo-rich fine precipitates within grains due to the presence of a high density of dislocations and the globally distributed dislocation cell structures, which served as heterogeneous nucleation sites for secondary phases. Along grain boundaries, a Mo-Cr-rich phase, observed in 750°C-aged conditions, displayed significant thermal coarsening. Throughout the aging process, various mechanisms, including stress relaxation, dislocation cell structure recovery, solution hardening, and precipitation hardening, competed to influence materials strength. These results contribute towards establishing the technical basis for qualifying LPBF 316H SS for advanced nuclear reactor applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Degradable Biocomposite Thermoplastic Polyurethanes

In this project, the team developed tough and degradable biocomposite thermoplastic polyurethanes (TPUs) by incorporating bacterial spores into TPUs as a biofunctional living filler. The team screened various bacteria and selected the Bacillus subtilis ATCC 6633 strain as the final candidate, primarily due to its genomic availability, sporulation ability and TPU assimilation activity. The heat-shock tolerance of ATCC 6633 spores was further improved through evolutionary engineering via Adaptive Laboratory Evolution (ALE), demonstrating a 17.7-fold enhanced germination efficiency post heat-shock treatment compared to the wild-type strain (WT). The team fabricated biocomposite TPUs by incorporating lyophilized powder of heat-shock tolerized (HST) spores during the hot melt extrusion (HME) of TPU at 135 °C. The baseline TPU used in this project is a commercially available soft-grade TPU (BCF45) manufactured by BASF. Colony forming unit (CFU) assays quantified that WT and HST spores in the TPU matrix retained approximately 20% and 100% survivability, respectively, after HME. Tensile testing demonstrated that the spores behaved as a polymer-reinforcing filler, positively affecting the overall tensile properties of the biocomposite TPU. For example, biocomposite TPU with WT and HST spores (BC TPU WT and BC TPU HST , respectively) exhibited up to 25% and 37% improved toughness, respectively, compared to TPU without spores. BC TPU HST showed remarkably improved disintegration in autoclaved compost (92% mass loss in 5 months), which simulated a microbially poor environment for TPU degradation. When compared to TPU without spores (44% mass loss in 5 months) the acceleration of degradation is marked. Respirometry confirmed that 72% of BC TPU HST was biomineralized into CO2 within 6 months, indicating that spores in the biocomposite TPU were germinated by utilizing nutrients in the autoclaved compost, facilitating TPU degradation at the end of the material's life. The team demonstrated the scale-up of biocomposite TPU fabrication using continuous extrusion and injection molding techniques. Processing conditions optimized in a lab-scale microcompounder were successfully transferred to a continuous extruder with a 30-fold increased throughput. Biocomposite TPUs prepared using these industry-relevant processes showed comparable toughness improvements to samples prepared in the lab-scale extruder. Excitingly, following compounding in the pilot-extruder the composite material could be injection molded, while retaining high spore viability and similar toughness improvements. The team also found that spores in biocomposite TPU served as antioxidants, preventing toughness decay during the recycled extrusion of BC TPU HST . Long-term storage tests over one year showed that the addition of spores had no negative effect on the longevity of the TPU. Furthermore, the team demonstrated the fabrication of spore-bearing biocomposite polymers with other polyesters such as PBAT, PLA, and PCL. We obtained promising preliminary data that showed overall toughness improvements for all polymers with spore addition. Finally, life cycle assessment (LCA) and techno-economic analysis (TEA) were carried out, which indicated minimal additional cost of fabrication. Overall, a tough and degradable biocomposite thermoplastic was successfully developed through this project, with all tasks completed successfully, achieving >100% of the objectives.

36 MATERIALS SCIENCE↗
NASA NTRS2002

Progress in the Development of Metamorphic Multi-Junction III-V Space-Solar Cells at Essential Research Incorporated

Theoretical calculations have shown that highest efficiency III-V multi-junction solar cells require alloy structures that cannot be grown on a lattice-matched substrate. Ever since the first demonstration of high efficiency metamorphic single junction 1.1 eV and 1.2 eV InGaAs solar cells by Essential Research Incorporated (ERI), interest has grown in the development of multi-junction cells of this type using graded buffer layer technology. ERI is currently developing a dual-junction 1.6 eV InGaP/1.1 eV InGaAs tandem cell (projected practical air-mass zero (AM0), one-sun efficiency of 28%, and 100-sun efficiency of 37.5%) under a Ballistic Missile Defense Command (BMDO) SBIR Phase II program. A second ongoing research effort at ERI involves the development of a 2.1 eV AlGaInP/1.6 eV InGaAsP/1.2 eV InGaAs triple-junction concentrator tandem cell (projected practical AM0 efficiency of 36.5% under 100 suns) under a SBIR Phase II program funded by the Air Force. We are in the process of optimizing the dual-junction cell performance. In case of the triple-junction cell, we have developed the bottom and the middle cell, and are in the process of developing the layer structures needed for the top cell. A progress report is presented in this paper.

Sinharoy, Samar↗
NASA NTRS2001

Extensional Rheology Experiment Developed to Investigate the Rheology of Dilute Polymer Solutions in Microgravity

A fundamental characteristic of fluid is viscosity; that is, the fluid resists forces that cause it to flow. This characteristic, or parameter, is used by manufacturers and end-users to describe the physical properties of a specific material so that they know what to expect when a material, such as a polymer, is processed through an extruder, a film blower, or a fiber-spinning apparatus. Normally, researchers will report a shear viscosity that depends on the rate of an imposed shearing flow. Although this type of characterization is sufficient for some processes, simple shearing experiments do not provide a complete picture of what a processor may expect for all materials. Extensional stretching flows are common in many polymer-processing operations such as extrusion, blow molding, and fiber spinning. Therefore, knowledge of the complete rheological (ability to flow and be deformed) properties of the polymeric fluid being processed is required to accurately predict and account for the flow behavior. In addition, if numerical simulations are ever able to serve as a priori design tools for optimizing polymer processing operations such as those described above, an accurate knowledge of the extensional viscosity of a polymer system and its variation with temperature, concentration, molecular weight, and strain rate is critical.

Logsdon, Kirk A.↗
NASA NTRS2005

Data-Analysis System for Entry, Descent, and Landing

A report describes the Entry Descent Landing Data Analysis (EDA), which is a system of signal-processing software and computer hardware for acquiring status data conveyed by multiple-frequency-shift-keying tone signals transmitted by a spacecraft during descent to the surface of a remote planet. The design of the EDA meets the challenge of processing weak, fluctuating signals that are Doppler-shifted by amounts that are only partly predictable. The software supports both real-time and post processing. The software performs fast-Fourier-transform integration, parallel frequency tracking with prediction, and mapping of detected tones to specific events. The use of backtrack and refinement parallel-processing threads helps to minimize data gaps. The design affords flexibility to enable division of a descent track into segments, within each of which the EDA is configured optimally for processing in the face of signal conditions and uncertainties. A dynamic-lock-state feature enables the detection of signals using minimum required computing power less when signals are steadily detected, more when signals fluctuate. At present, the hardware comprises eight dual-processor personal-computer modules and a server. The hardware is modular, making it possible to increase computing power by adding computers.

Pham, Timothy↗
DOE OSTI2020

Investigation of the benefits of diabatic microreactors for process intensification of the water-gas shift reaction within the steam reforming process

Presently, the steam reforming process is the largest industrial source of hydrogen. Improving its efficiency can help to reduce associated carbon emissions and hydrogen production costs. Intensifying the water-gas shift reaction using microreactors with integrated cooling is one way of achieving this. In this study, a 2-D computational model of one of these microreactors is developed, validated with experimental data, and then used to demonstrate how microreactors can enhance the conversion of the water-gas shift reaction beyond what can be achieved using conventional packed bed reactors. These results are then generalized into a full system model of the steam reforming process to demonstrate how microreactors can reduce hydrogen production costs. The results suggest that microreactors can significantly reduce the required reactor volume and catalyst loading for the water-gas shift reaction and can similarly reduce the hydrogen production costs associated with the steam reforming process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

AEOLUS: Advances in Experimental Design, Optimal Control, and Learning for Uncertain Complex Systems

Sustained advances in the mathematics of modeling and simulation have resulted in the capability today for routine simulation of a number of large scale complex DOE-relevant systems. As remarkable as this capability for solving the so-called forward problem is, it is typically only the first step-an inner loop within an outer loop that explores the simulation model's parameter space and decision space to characterize uncertainty in the model's predictions, learn unknown model parameters from data, design the most informative experiments, determine optimal control strategies, and create optimal designs. Broadly, what unifies all of these outer loop problems is that they are, in one form or another, optimization problems over parameter/control/design space that are constrained by complex uncertain models. To fully realize the power of scientific simulation as a basis for scientific discovery, technological innovation, and rational decision-making, it is imperative to move beyond simulation to tackle the outer loop of optimization for learning from data, experimental design, and control with complex uncertain models. When the models under consideration are large-scale and complex, and when the optimization variable and uncertain parameter spaces are high (or infinite) dimensional, this constitutes a grand challenge of the highest order, and is intractable with conventional methods. To overcome these challenges, the AEOLUS Center was established to develop a unified mathematical, computational, and statistical framework for (1) Learning predictive models from complex data via Bayesian inference and optimization, and (2) Optimizing experiments, processes, and designs using the resulting uncertain models. These problems are intractable with conventional methods, for several reasons: (1) The simulation problems that govern the inner loops of the optimization problems are expensive to execute (due to severe nonlinearity, heterogeneity, multiphysics/multiscale coupling); (2) The optimization variable and uncertain parameter spaces are high dimensional, often stemming from discretizations of infinite dimensional fields such as initial conditions, sources, or material properties. We argue that the key to overcoming these challenges is to develop new mathematical, computational, and statistical methods that exploit the structure of the Bayesian inference and optimization problems mediated by their underlying complex uncertain models. This structure includes the regularity, sparsity, geometry, low intrinsic dimensionality, and multifidelity nature of the maps from uncertain parameter/optimization variable spaces to the specific objectives targeted: Bayesian inference, optimal experimental design, and optimal control design. Black box methods developed as generic tools are incapable of exploiting this structure. To be successful, we must create, integrate, and cross-fertilize ideas across multiple areas of applied math--including approximation theory, Bayesian inference, data science, experimental design, information theory, machine learning, model reduction, optimal control theory, parallel algorithms, PDE-constrained optimization, randomized algorithms, stochastic optimization, and uncertainty quantification--all while exploiting the structure of the problems at hand. With this goal in mind, we have marshaled a team of leading authorities in these areas. While the methods we develop will be broadly applicable across a wide spectrum of DOE problems in which experiments inform models and the systems those models describe must be optimized under uncertainty, we have chosen a specific area, advanced manufacturing and materials, to drive our work. AMM is characterized by complex models across multiple scales, and is a rich source of challenging problems in inference, experimental design, and optimal control, requiring multifaceted and integrated advances in applied mathematics. As such, AMM serves as an excellent vehicle to motivate and demonstrate the advances in applied mathematics developed by our center.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1996

Computer-Aided Process Model For Carbon/Phenolic Materials

Computer program implements thermochemical model of processing of carbon-fiber/phenolic-matrix composite materials into molded parts of various sizes and shapes. Directed toward improving fabrication of rocket-engine-nozzle parts, also used to optimize fabrication of other structural components, and material-property parameters changed to apply to other materials. Reduces costs by reducing amount of laboratory trial and error needed to optimize curing processes and to predict properties of cured parts.

Letson, Mischell A.↗
DOE OSTI2024

Development of a Chemistry-Based Isotherm Model and Techno-Economic Optimization of a Moving Bed Process for CO2 Capture Using a Functionalized Metal-Organic Framework

Amine-appended metal-organic frameworks of the class Mg2(dobpdc) are promising candidates for efficient carbon capture in part due to their step-shaped CO2 adsorption behavior. However, the existing isotherm models are lacking as they are unable to capture the complicated chemisorption mechanisms which are still not well known for these materials. Here, a chemistry-based isotherm model is developed and fit to experimental CO2 adsorption data for dmpn-Mg2(dobpdc). Reactions for a cooperative adsorption mechanism are proposed, and the reaction pathway is optimally selected. The chemistry-based model shows an improvement in prediction by a factor of 6 when compared to a recent isotherm model in literature. A plant-wide model is developed for a moving bed based adsorber/desorber and techno-economic optimization is performed. For likely values of price and lifespan, the moving bed process gives a significant improvement in economics when compared to a fixed bed contactor process and a traditional MEA capture system.

carbon capture↗
DOE OSTI2024

Enhanced prediction of Cs removal by CST from Hanford tank waste with K accountability

Abstract The treatment of Hanford tank waste is one of the most challenging environmental cleanup activities to date. To expedite the processing of liquid waste stored in underground tanks in Washington State it is necessary to remove the significant dose contributor, 137 Cs. Crystalline silicotitanate ion exchanger is currently used to remove 137 Cs from the aqueous phase of Hanford tank wastes in preparation for vitrification at the Waste Treatment and Immobilization Plant (WTP). Improving the understanding of potassium impacts on ion exchange behavior of Cs will help in the operation of a critical component of one of the most complex treatment processes in the world today. Optimization of this process can result in significant cost savings and less waste production. Toward this effort, a series of batch contact tests varied in potassium concentration were conducted to look at the impact of potassium concentration on Cs distribution. Experimental distribution ratios ( K d ) were compared to the distribution ratios predicted using the ZAM model. A significant underprediction of Cs capacity in the presence of potassium was seen with the existing model. A revision of the equilibrium constants was determined and provided a statistically better fit for determining the Cs K d values in tank waste matrices.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1991

Automated carbon dioxide cleaning system

Solidified CO2 pellets are an effective blast media for the cleaning of a variety of materials. CO2 is obtained from the waste gas streams generated from other manufacturing processes and therefore does not contribute to the greenhouse effect, depletion of the ozone layer, or the environmental burden of hazardous waste disposal. The system is capable of removing as much as 90 percent of the contamination from a surface in one pass or to a high cleanliness level after multiple passes. Although the system is packaged and designed for manual hand held cleaning processes, the nozzle can easily be attached to the end effector of a robot for automated cleaning of predefined and known geometries. Specific tailoring of cleaning parameters are required to optimize the process for each individual geometry. Using optimum cleaning parameters the CO2 systems were shown to be capable of cleaning to molecular levels below 0.7 mg/sq ft. The systems were effective for removing a variety of contaminants such as lubricating oils, cutting oils, grease, alcohol residue, biological films, and silicone. The system was effective on steel, aluminum, and carbon phenolic substrates.

Hoppe, David T.↗
NASA NTRS2010

Platform for Post-Processing Waveform-Based NDE

Signal- and image-processing methods are commonly needed to extract information from the waves, improve resolution of, and highlight defects in an image. Since some similarity exists for all waveform-based nondestructive evaluation (NDE) methods, it would seem that a common software platform containing multiple signal- and image-processing techniques to process the waveforms and images makes sense where multiple techniques, scientists, engineers, and organizations are involved. NDE Wave & Image Processor Version 2.0 software provides a single, integrated signal- and image-processing and analysis environment for total NDE data processing and analysis. It brings some of the most useful algorithms developed for NDE over the past 20 years into a commercial-grade product. The software can import signal/spectroscopic data, image data, and image series data. This software offers the user hundreds of basic and advanced signal- and image-processing capabilities including esoteric 1D and 2D wavelet-based de-noising, de-trending, and filtering. Batch processing is included for signal- and image-processing capability so that an optimized sequence of processing operations can be applied to entire folders of signals, spectra, and images. Additionally, an extensive interactive model-based curve-fitting facility has been included to allow fitting of spectroscopy data such as from Raman spectroscopy. An extensive joint-time frequency module is included for analysis of non-stationary or transient data such as that from acoustic emission, vibration, or earthquake data.

Roth, Don J.↗