SEARCH · Search NASA

Results for “analytical process”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 379 records · Page 21

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Liquid-to-gas transfer of sodium in a liquid cathode glow discharge

Abstract Plasma-liquid interactions have been extensively studied with a focus on the transport of reactive species from the plasma to the liquid phase and their induced liquid phase chemistry and resulting applications. While solute transfer from the liquid to the gas phase in plasmas has been widely used in analytical chemistry, the underlying processes remain relatively unexplored. We report spatially and temporally resolved absolute density measurements of sodium in a plasma with a NaCl solution cathode using two-photon absorption laser induced fluorescence (TaLIF). The observed non-linear increase in sodium density with solution conductivity is shown to correlate with droplet generation as visualized by Mie scattering. The findings are explained by droplet generation by electrospray induced by Taylor cone formation as underpinning mechanism for the introduction of sodium in the plasma. An analytical sheath model combined with a scaling law shows an increase in electric field force with solution conductivity that is consistent with the observed non-linear increase in sodium density in the plasma with solution conductivity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Quantification of Hydrogen Isotopes Utilizing Raman Spectroscopy Paired with Chemometric Analysis for Application across Multiple Systems

On-line and real-time analysis of a chemical process is a major analytical challenge that can drastically change the way the chemical industry or chemical research operates. With in situ analyses, new and powerful understanding of chemistry can be gained; however, building robust tools for long-term monitoring faces many challenges that include compensating for instrument drift, instrument replacement, and sensor or probe replacement. Accounting for these changes by recollecting calibration data and rebuilding quantification models can be costly and time consuming. Here, in this study, methods to overcome these challenges are demonstrated with an application of Raman spectroscopy to monitoring hydrogen isotopes with varied speciation within dynamic gas streams. Specifically, chemical data science tools such as chemometric modeling are leveraged along with several examples of calibration transfer approaches. Furthermore, the optimization of instrument and sensors cell parameters for targeted gas phase analyses is discussed. While the particular focus on hydrogen is highly beneficial within the nuclear energy sector, mechanisms built and demonstrated here are widely applicable to optical spectroscopy monitoring in numerous other chemical systems that can be leveraged in other hazardous processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Functional metal–organic frameworks as effective sensors of gases and volatile compounds

Developing efficient sensor materials with superior performance for selective, fast and sensitive detection of gases and volatile organic compounds (VOCs) is essential for human health and environmental protection, through monitoring indoor and outdoor air pollutions, managing industrial processes, controlling food quality and assisting early diagnosis of diseases. Metal–organic frameworks (MOFs) are a unique type of crystalline and porous solid material constructed from metal nodes (metal ions or clusters) and functional organic ligands. They have been investigated extensively for possible use as high performance sensors for the detection of many different gases and VOCs in recent years, due to their large surface area, tunable pore size, functionalizable sites and intriguing properties, such as electrical conductivity, magnetism, ferroelectricity, luminescence and chromism. The high porosity of MOFs allows them to interact strongly with various analytes, including gases and VOCs, thus resulting in easily measurable responses to different physicochemical parameters. Although much of the recent work on MOF-based luminescent sensors have been summarized in several excellent reviews (up to 2018), a comprehensive overview of these materials for sensing gases and VOCs based on chemiresistive, magnetic, ferroelectric, and colorimertic mechanisms is missing. In this review, we highlight the most recent progress in developing MOF sensing and switching materials with an emphasis on sensing mechanisms based on electricity, magnetism, ferroelectricity and chromism. We provide a comprehensive analysis on the MOF–analyte interactions in these processes, which play a key role in the sensing performance of the MOF-based sensors and switches. We discuss in detail possible applications of MOF-based sensing and switching materials in detecting oxygen, water vapor, toxic industrial gases (such as hydrogen sulfide, ammonia, sulfur dioxide, nitrous oxide, carbon oxides and carbon disulfide) and VOCs (such as aromatic and aliphatic hydrocarbons, ketones, alcohols, aldehydes, chlorinated hydrocarbons and N,N'-dimethylformamide). Altogether, this review serves as a timely source of information and provides insight for the future development of advanced MOF materials as next-generation gas and VOC sensors.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Construction of a Code Verification Matrix for Heat Conduction With Finite Element Code Applications

When establishing the pedigree of a simulation tool, code verification is used to ensure that the implemented numerical algorithm is a faithful representation of its underlying mathematical model. During this process, numerical results on various meshes are systematically compared to a reference analytic solution. The selection of analytic solutions can be a laborious process, as it is difficult to establish adequate code confidence without performing redundant work. In this report we address this issue by applying a physics-based process that establishes a set of reference problems. In this process, code simulation options are categorized and systematically tested, which ensures that gaps in testing are easily identified and addressed. The resulting problems are primarily intended for code verification analysis but may also be useful for comparison to other simulation codes, troubleshooting activities, or training exercises. The process is used to select fifteen code verification problems relevant for the one-dimensional steady-state heat conduction equation. These problems are applicable to a wide variety of simulation tools, but, in this work, a demonstration is performed using the finite element-based nuclear fuel performance code BISON. Convergence to the analytic solution at the theoretical rate is quantified for a selection of the problems, which establishes a baseline pedigree for the code. Not only can this standard set of conduction solutions be used for verification of other codes, but also the physics-based process for selecting problems can be utilized to quantify and expand testing for any simulation tool.

42 ENGINEERING↗

DOE OSTI2024

Automated Framework for Groundwater Monitoring Using DWT with LSTM and Transformers

Environmental monitoring is critical for safeguarding public health and ecological well-being. Traditional data structuring and workflow monitoring methods consume significant time and effort, hindering timely insights and effective decision-making. Our study addresses this challenge by presenting an AI framework that automates data cleaning, structuring, and modeling processes, specifically targeting applications in groundwater monitoring. By leveraging automation for data processing and model training, our framework establishes a novel and efficient paradigm for environmental monitoring, with its potential application to the vast network of over a hundred Department of Energy Environmental Management (DoE-EM) cleanup sites across the country. It analyzes data streams from a network of groundwater Internet-of-Things (IoT) sensors deployed at the Savannah River Site (SRS) for prediction modeling. This allows human experts to focus on analysis and decision-making, ultimately leading to better environmental outcomes.The framework employs multivariate time-series forecasting methods to study and model the behavior of varying chemical analytes. The continuous learning process is enabled by utilizing deep learning techniques. It allows the framework to become more nuanced in its analysis over time, adapting to the specific characteristics of the environmental site and the evolving nature of contaminant behavior. Deep learning models known for sequence modeling, LSTM, and Transformers are employed for time series forecasting. Data processing and structuring are essential components significantly impacting the final model's performance. This hypothesis was proven by presenting a comparative analysis of model performance with processed and unprocessed data. The feature engineering approach utilized was the Discrete Wavelet Transform, which works well with time series data.

Discrete Wavelet Transform (DWT)↗

DOE OSTI2021

Determination of Carbon Functional Groups in Pyrolysis Bio-Oils using 13 C NMR: Laboratory Analytical Procedure (LAP)

Pyrolysis is a process that can be used to convert biomass to solid, liquid and gaseous products for use as renewable chemicals and fuels. The liquid fraction, known as “bio-oil” is complex and challenging to characterize, particularly by means of GC/MS, GPC, LC and FT-IR. NMR is capable of analyzing whole bio-oil samples and can provide quantitative results to characterize different functional groups or types of carbon present in bio-oil. This Laboratory Analytical Procedure (LAP) quantifies different carbon functional groups in whole bio-oil samples. This information can be used for comparisons between different pyrolysis experimental conditions or different upgrading processes and catalysts, and also allow for comparisons between bio-oils produced at different facilities.

09 BIOMASS FUELS↗

NASA NTRS2016

Composite Cure Process Modeling and Simulations using COMPRO(Registered Trademark) and Validation of Residual Strains using Fiber Optics Sensors

Composite cure process induced residual strains and warping deformations in composite components present significant challenges in the manufacturing of advanced composite structure. As a part of the Manufacturing Process and Simulation initiative of the NASA Advanced Composite Project (ACP), research is being conducted on the composite cure process by developing an understanding of the fundamental mechanisms by which the process induced factors influence the residual responses. In this regard, analytical studies have been conducted on the cure process modeling of composite structural parts with varied physical, thermal, and resin flow process characteristics. The cure process simulation results were analyzed to interpret the cure response predictions based on the underlying physics incorporated into the modeling tool. In the cure-kinetic analysis, the model predictions on the degree of cure, resin viscosity and modulus were interpreted with reference to the temperature distribution in the composite panel part and tool setup during autoclave or hot-press curing cycles. In the fiber-bed compaction simulation, the pore pressure and resin flow velocity in the porous media models, and the compaction strain responses under applied pressure were studied to interpret the fiber volume fraction distribution predictions. In the structural simulation, the effect of temperature on the resin and ply modulus, and thermal coefficient changes during curing on predicted mechanical strains and chemical cure shrinkage strains were studied to understand the residual strains and stress response predictions. In addition to computational analysis, experimental studies were conducted to measure strains during the curing of laminated panels by means of optical fiber Bragg grating sensors (FBGs) embedded in the resin impregnated panels. The residual strain measurements from laboratory tests were then compared with the analytical model predictions. The paper describes the cure process procedures and residual strain predications, and discusses pertinent experimental results from the validation studies.

Sreekantamurthy, Thammaiah↗

DOE OSTI2022

Building Analytics Tool Deployment at Scale: Benefits, Costs, and Deployment Practices

Buildings are becoming more data-rich. Building analytics tools, including energy information systems (EIS) and fault detection and diagnostic (FDD) tools, have emerged to enable building operators to translate large amounts of time-series data into actionable findings to achieve energy and non-energy benefits. To expedite data analytics adoption and facilitate technology innovation, building owners, technology developers, and researchers need reliable cost–benefit data and evidence-based guidance on deployment practices. This paper fulfills these needs with the energy use and survey data from a wide-ranging research and industry partnership program that covers thousands of buildings installed with analytics tools. The paper indicates that after two years of implementation, organizations using FDD tools and EIS tools achieved 9% and 3% median annual energy savings, respectively. The median base cost and annual recurring cost for FDD are USD 0.65 per square meter (m2) (USD 0.06 per square foot [ft2]) and USD 0.22 per m2 (USD 0.02 per ft2), and are USD 0.11 per m2 (USD 0.01 per ft2) and USD 0.11 per m2 (USD 0.01 per ft2) for EIS. The common metrics and analyses that are used in the tools to support the discovery of energy efficiency measures are summarized in detail. Two best practice examples identified to maximize the benefits of tool implementation are also presented. Opportunities to advance the state of technology include simplified data integration and management, and more efficient processes for acting on analytics outputs. Compared with previous efforts in the literature, the findings presented in this paper demonstrate the effectiveness of building analytics tools with the largest known dataset.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2000

The ISS EXPRESS Rack: An Innovative Approach of Rapid Integration

The EXpedite the PRocessing of Experiments to Space Station or EXPRESS Rack System, was developed to provide Space Station accommodations for small, subrack payloads. The EXPRESS Rack accepts Space Shuttle middeck locker type payloads and International Subrack Interface Standard (ISIS) Drawer payloads, allowing previously flown payloads an opportunity to transition to the International Space Station. The EXPRESS Rack provides power, data, command and control, video, water cooling, air cooling, vacuum exhaust, and Nitrogen supply to payloads. The EXPRESS Rack system also includes transportation racks to transport payloads to and from the Space Station, Suitcase Simulators to allow a payload developer to verify power and data interfaces at the development site, Functional Checkout Units to allow Payload checkout at KSC prior to launch, and trainer racks for the astronauts to learn how to operate the EXPRESS Racks prior to flight. Standard hardware and software interfaces provided by the EXPRESS Rack simplify the analytical and physical integration processes, and facilitates simpler ISS payload development. The EXPRESS Rack has also formed the basis for the U.S. Life Sciences payload racks and the Window Observational Research Facility on Space Station.

Sledd, Annette M.↗

NASA NTRS1999

EXPRESS Rack Overview

Sledd, Annette M.↗

NASA NTRS2012

Self-Sealing Wet Chemistry Cell for Field Analysis

In most analytical investigations, there is a need to process complex field samples for the unique detection of analytes, especially when detecting low concentration organic molecules that may identify extraterrestrial life. Wet chemistry based instruments are the techniques of choice for most laboratory- based analysis of organic molecules due to several factors including less fragmentation of fragile biomarkers, and ability to concentrate target species resulting in much lower limits of detection. Development of an automated wet chemistry preparation system that can operate autonomously on Earth and is also designed to operate under Martian ambient conditions will demonstrate the technical feasibility of including wet chemistry on future missions. An Automated Sample Processing System (ASPS) has recently been developed that receives fines, extracts organics through solvent extraction, processes the extract by removing non-organic soluble species, and delivers sample to multiple instruments for analysis (including for non-organic soluble species). The key to this system is a sample cell that can autonomously function under field conditions. As a result, a self-sealing sample cell was developed that can autonomously hermetically seal fines and powder into a container, regardless of orientation of the apparatus. The cap is designed with a beveled edge, which allows the cap to be self-righted as the capping motor engages. Each cap consists of a C-clip lock ring below a crucible O-ring that is placed into a groove cut into the sample cap.

Beegle, Luther W.↗

NASA NTRS1993

Influence of test configuration on the combustion characteristics of polymers as ignition sources

The experimental evaluation of polymers as ignition sources for metals was accomplished at the NASA White Sands Test Facility (WSTF) using a standard promoted combustion test. These tests involve the transient burning of materials in high-pressure oxygen environments. They have provided data from which design decisions can be made; data include video recordings of ignition and non-ignition for specific combinations of metals and polymers. Other tests provide the measured compositions of combustion products for polymers at select burn times and an empirical basis for estimating burn rates. With the current test configuration, the detailed analysis of test results requires modeling a three-dimensional, transient convection process involving fluid motion, thermal conduction and convection, the diffusion of chemical species, and the erosion of sample surface. At the high pressure extremes, it even requires the analysis of turbulent, transient convection where the physics of the problem are not well known and the computation requirements are not practical at this time. An alternative test configuration that can be analyzed with a relatively-simple convection model was developed during the summer period. The principal change constitutes replacing a large-diameter polymer disk at the end of the metal test rod with coaxial polymer cylinders that have a diameter nearer to that of the metal rod. The experimental objective is to assess the importance of test geometries on the promotion of metal ignition by testing with different lengths of the polymer and, with an extended effort, to analyze the surface combustion in the redesigned promoted combustion tests through analytical modeling of the process. The analysis shall use the results of cone-calorimeter tests of the polymer material to model primary chemical reactions and, with proper design of the promoted combustion test, modeling of the convection process could be conveniently limited to a quasi-steady boundary layer analysis where the economical solution of parabolic equations is involved. The products for the summer period are: (1) a conceptual-level redesign of the test apparatus, and (2) the development and use of an approximate integral boundary layer analysis to demonstrate the influence of geometry changes prior to testing. A computer code STAN5, an accurate numerical boundary layer model whose earlier versions were developed for the NASA Lewis Research Center by the Fellow, also was installed and validated on the WSTF and New Mexico State University computer systems as a starting point in the development of a more detailed fluid mechanics and combustion model.

Julien, Howard L.↗

NASA NTRS1993

Risk management for the Space Exploration Initiative

Probabilistic Risk Assessment (PRA) is a quantitative engineering process that provides the analytic structure and decision-making framework for total programmatic risk management. Ideally, it is initiated in the conceptual design phase and used throughout the program life cycle. Although PRA was developed for assessment of safety, reliability, and availability risk, it has far greater application. Throughout the design phase, PRA can guide trade-off studies among system performance, safety, reliability, cost, and schedule. These studies are based on the assessment of the risk of meeting each parameter goal, with full consideration of the uncertainties. Quantitative trade-off studies are essential, but without full identification, propagation, and display of uncertainties, poor decisions may result. PRA also can focus attention on risk drivers in situations where risk is too high. For example, if safety risk is unacceptable, the PRA prioritizes the risk contributors to guide the use of resources for risk mitigation. PRA is used in the Space Exploration Initiative (SEI) Program. To meet the stringent requirements of the SEI mission, within strict budgetary constraints, the PRA structure supports informed and traceable decision-making. This paper briefly describes the SEI PRA process.

Buchbinder, Ben↗

DOE OSTI2024

Improving and Automating Building Model Data Exchange

There are many instances throughout a project’s lifecycle where there arises a need for quick and accurate risk assessment of building designs. For example, an unexpected design change during construction may necessitate structural engineers to perform a seismic risk assessment on analytical models of the updated building design using high fidelity structural analysis software, such as ANSYS or Abaqus. However, the efficiency of such workflows often depends upon the interoperability of architectural design software and structural analysis software. When the quality of this interoperability is lacking or even non-existent, the efficiency of virtual engineering workflows is hampered, which increases project costs. A McGraw Hill industry survey of professional users of Building Information Modeling (BIM) technologies found that there is high demand for BIM interoperability for structural analysis, but that the value/difficulty ratio is currently too low for practical use. There have been efforts by the academic community to facilitate model data exchange between the architectural design and structural analysis domains, but such solutions have not been widely adopted by industry, face technical challenges, and oftentimes are limited in applicability for users of various BIM software. Therefore, INL is developing capabilities to improve, automate, and generalize model data exchange between architectural BIM software (e.g., Revit) and structural analysis software (e.g., SAP2000, ANSYS). The goal is to help expedite and automate as much of the pre-processing step for creating analytical models in finite element analysis software as reasonably as possible. Such a "BIM-to-FEA" conversion tool should provide direct benefit to end-users through accuracy, automation, quick turn-around, and wide applicability. To generalize the application of this BIM-to-FEA conversion tool and increase its useability among the many different commercial BIM software currently used by industry, the program is being developed with the concept of openBIM. OpenBIM is the application of non-proprietary, open data standards that allow for BIM model data exchange in a format that is accessible, retainable, and useable for all users. The most widely used open, non-proprietary data exchange format for BIM is the Industry Foundation Classes (IFC) schema. IFC is developed by buildingSMART international and is ISO certified (ISO 16739-1:2018). The BIM-to-FEA conversion tool is being developed for compatibility with typical commercial building designs of steel framed structures. The tool is currently capable of importing architectural BIM data of framed building structures, recognizing and extracting the aspects of the model that are required for structural analysis, adjusting the connectivity of frame members, and finally exporting to an analytical model stored in the IFC format. The exported IFC analytical model can then be imported into various openBIM compliant software, such as SAP2000. Such capabilities have already been tested on commercial software, as shown above, and continue to be improved. Work is underway to test the conversion on various commercial BIM software, develop a user-friendly interface, incorporate the program into the broader DeepLynx data warehouse project being developed by INL, and to eventually open-source the tool for the benefit of the community. Future development of the tool envisions the ability for efficient iterative risk assessment of generative building designs, all within a workflow utilizing open-source tools. One such open-source tool will be MOOSE, an advanced finite element analysis tool developed at INL. The conversion tool will also branch out from typical commercial building designs and will aim to incorporate nuclear construction. The aim will be to convert both structural and non-structural components of nuclear facilities, such as curved concrete containment structures and piping systems, respectively.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2005

Development of the Architectural Simulation Model for Future Launch Systems and its Application to an Existing Launch Fleet

A significant portion of lifecycle costs for launch vehicles are generated during the operations phase. Research indicates that operations costs can account for a large percentage of the total life-cycle costs of reusable space transportation systems. These costs are largely determined by decisions made early during conceptual design. Therefore, operational considerations are an important part of vehicle design and concept analysis process that needs to be modeled and studied early in the design phase. However, this is a difficult and challenging task due to uncertainties of operations definitions, the dynamic and combinatorial nature of the processes, and lack of analytical models and the scarcity of historical data during the conceptual design phase. Ultimately, NASA would like to know the best mix of launch vehicle concepts that would meet the missions launch dates at the minimum cost. To answer this question, we first need to develop a model to estimate the total cost, including the operational cost, to accomplish this set of missions. In this project, we have developed and implemented a discrete-event simulation model using ARENA (a simulation modeling environment) to determine this cost assessment. Discrete-event simulation is widely used in modeling complex systems, including transportation systems, due to its flexibility, and ability to capture the dynamics of the system. The simulation model accepts manifest inputs including the set of missions that need to be accomplished over a period of time, the clients (e.g., NASA or DoD) who wish to transport the payload to space, the payload weights, and their destinations (e.g., International Space Station, LEO, or GEO). A user of the simulation model can define an architecture of reusable or expendable launch vehicles to achieve these missions. Launch vehicles may belong to different families where each family may have it own set of resources, processing times, and cost factors. The goal is to capture the required resource levels of the major launch elements and their required facilities. The model s output can show whether or not a certain architecture of vehicles can meet the launch dates, and if not, how much the delay cost would be. It will also produce aggregate figures of missions cost based on element procurement cost, processing cost, cargo integration cost, delay cost, and mission support cost. One of the most useful features of this model is that it is stochastic where it accepts statistical distributions to represent the processing times mimicking the stochastic nature of real systems.

Rabadi, Ghaith↗

NASA NTRS1984

Physical processes in the strong magnetic fields of accreting neutron stars

Analytical formulae are fitted to observational data on physical processes occurring in strong magnetic fields surrounding accreting neutron stars. The propagation of normal modes in the presence of a quantizing magnetic field is discussed in terms of a wave equation in Fourier space, quantum electrodynamic effects, polarization and mode ellipticity. The results are applied to calculating the Thomson scattering, bremsstrahlung and Compton scattering cross-sections, which are a function of the frequency, angle and polarization of the magnetic field. Numerical procedures are explored for solving the radiative transfer equations. When applied to modeling X ray pulsars, a problem arises in the necessity to couple the magnetic angle and frequency dependence of the cross-sections with the hydrodynamic equations. The use of time-dependent averaging and approximation techniques is indicated.

Meszaros, P.↗

DOE OSTI2021

Mass action model of solution activity via speciation by solvation and ion pairing equilibria

Abstract Solutes and their concentrations influence many natural and anthropogenic solution processes. Electrolyte and solution models are used to quantify and predict such behavior. Here we present a mechanistic solution model based on mass action equilibria. Solvation and ion pairing are used to model speciated solute and solvent concentrations such that they correlate to a solution’s vapor pressure (solvent activity) according to Raoult’s law from dilute conditions to saturation. This model introduces a hydration equilibrium constant ( K ha ) that is used with either an ion dissociation constant ( K id ) or a hydration modifier ( m ) with an experimentally determined ion dissociation constant, as adjustable parameters to fit vapor–liquid equilibrium data. The modeled solvation equilibria are accompanied by molecular dynamics (MD) studies that support a decline in the observed degree of solvation with increased concentration. MD calculations indicate this finding is a combination of a solvent that solvates multiple solutes, and changes in a solute’s solvation sphere, with the dominant factor changing with concentration. This speciation-based solution model is lateral to established electrostatics-based electrolyte theories. With its basis in mass action, the model can directly relate experimental data to the modeled solute and solvent speciated concentrations and structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Corrosivity Screening of Pyrolysis Bio-Oils by Short-Term Alloy Exposures. Laboratory Analytical Procedure (LAP), Issue Date: May 12, 2022

Bio-oils contain organic acids and oxygenated compounds that can lead to corrosion issues during bio-oil processing and storage. This Laboratory Analytical Procedure (LAP) allows for rapid screening of a bio-oil's corrosivity without the need for complex equipment and long-term exposures. A robust and repeatable method for assessing the corrosivity of bio-oils is necessary in order to remove materials degradation as an obstacle to research, upgrading, use and storage of bio-oils. This LAP involves the incubation of a representative alloy, 410 stainless steel (410 SS), specimen in bio-oil over a period of 48 hours at 50 degrees C in a sealed container. The corrosive species in the bio-oil react with and deplete alloy elements such as iron (Fe) and/or chromium (Cr) from the specimen into the bio-oil solution. The depletion of Fe and Cr from the specimen results in a significant mass loss that can be recorded. The mass loss is directly correlated to the corrosivity of a bio-oil. Examples of bio-oils in scope include the ones produced by fast pyrolysis and catalytic fast pyrolysis, as well as liquids produced from hydrothermal liquefaction.

09 BIOMASS FUELS↗