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At least 937 records · Page 52

Electrochemical, Polarization, and Crevice Corrosion Testing of Inconel X750: A Supplement to the Environmental Control and Life Support System Sustaining Metal Materials Compatibility Study

In previous studies, electrochemical test results were experimentally acquired and then presented for several noble alloys in two specific solutions representative of waste liquids generated or present within the Environmental Control and Life Support System (ECLSS) aboard the International Space Station (ISS). Subsequently, another metal candidate, Inconel X750, has been submitted and was subjected to the same test routines in the same solutions and evaluated with the same statistical/analytical methodologies as those utilized in the earlier studies. Previous studies included three titanium grades, (Commercially Pure, 6Al-4V alloy, and 6Al-4V Low Interstitial alloy), two nickel-chromium alloys (Inconel® 625 and Hastelloy® C276), one high tier stainless steel (Cronidur® 30), and a nickel-titanium alloy (Nitinol 60). Thus far, all candidate alloys have exhibited excellent corrosion protection and galvanic compatibility attributes and have been deemed qualified materials for application within the ECLSS facility. Inconel X750 now joins that group. The titanium alloys gave the best results of all the metal candidates by demonstrating superior nobility and galvanic protection properties. It is worth noting that the corrosion performance properties for the three titanium alloys were essentially indistinguishable. As such and for expediency, this study and all future evaluations will refer only to the comparative properties already documented for Titanium 6Al-4V as this alloy is representative of all three alloys and considered to be more mainstream. Now the measured corrosion properties for Inconel X750 were very similar to those determined previously for Inconel 625 and Hastelloy C276 which were also determined to be very high performers. For the current effort, the results have clearly shown that Inconel X750 possesses exceptional anti-corrosion attributes comparable to metals in the highest tier of the galvanic series. Overall, one can conclude that Inconel X750 is quite noble, highly corrosion resistant and galvanically compatible with the other metal groups from both an electrochemical perspective and a long-term exposure scenario. This was clearly demonstrated after utilizing the same techniques as those applied in previous studies which included linear, Tafel and cyclic polarization, galvanic coupling with each of the other metal candidates, and pitting/crevicing assessments after one full year of immersion in the subject test solutions. Attributes defining the nobility and anti-corrosion capabilities for X750 appear to be on par with all the other candidates thus far and this alloy can now be classified as ‘excellent’ exhibiting very high resistance toward general, localized, and galvanic corrosion in the subject test media.

Lee, R. E.↗

Aerosol Absorption in Global Models From AeroCom Phase III

Aerosol-induced absorption of shortwave radiation can modify the climate through local atmospheric heating, which affects lapse rates, precipitation, and cloud formation. Presently, the total amount of aerosol absorption is poorly constrained, and the main absorbing aerosol species (black carbon (BC), organic aerosols (OA), and mineral dust) are diversely quantified in global climate models. As part of the third phase of the Aerosol Comparisons between Observations and Models (AeroCom) intercomparison initiative (AeroCom phase III), we here document the distribution and magnitude of aerosol absorption in current global aerosol models and quantify the sources of intermodel spread, highlighting the difficulties of attributing absorption to different species. In total, 15 models have provided total present-day absorption at 550 nm (using year 2010 emissions), 11 of which have provided absorption per absorbing species. The multi-model global annual mean total absorption aerosol optical depth (AAOD) is 0.0054 (0.0020 to 0.0098; 550 nm), with the range given as the minimum and maximum model values. This is 28 % higher compared to the 0.0042 (0.0021 to 0.0076) multi-model mean in AeroCom phase II (using year 2000 emissions), but the difference is within 1 standard deviation, which, in this study, is 0.0023 (0.0019 in Phase II). Of the summed component AAOD, 60 % (range 36 %–84 %) is estimated to be due to BC, 31 % (12 %–49 %) is due to dust, and 11 % (0 %–24 %) is due to OA; however, the components are not independent in terms of their absorbing efficiency. In models with internal mixtures of absorbing aerosols, a major challenge is the lack of a common and simple method to attribute absorption to the different absorbing species. Therefore, when possible, the models with internally mixed aerosols in the present study have performed simulations using the same method for estimating absorption due to BC, OA, and dust, namely by removing it and comparing runs with and without the absorbing species. We discuss the challenges of attributing absorption to different species; we compare burden, refractive indices, and density; and we contrast models with internal mixing to models with external mixing. The model mean BC mass absorption coefficient (MAC) value is 10.1 (3.1 to 17.7) m 2 g −1 (550 nm), and the model mean BC AAOD is 0.0030 (0.0007 to 0.0077). The difference in lifetime (and burden) in the models explains as much of the BC AAOD spread as the difference in BC MAC values. The difference in the spectral dependency between the models is striking. Several models have an absorption Ångstrøm exponent (AAE) close to 1, which likely is too low given current knowledge of spectral aerosol optical properties. Most models do not account for brown carbon and underestimate the spectral dependency for OA.

Aerosol absorption↗

Synthesizing Disparate LiDAR and Satellite Datasets through Deep Learning to Generate Wall-to-Wall Regional Inventories for the Complex, Mixed-Species Forests of the Eastern United States

Light detection and ranging (LiDAR) has become a commonly-used tool for generating remotely-sensed forest inventories. However, LiDAR-derived forest inventories have remained uncommon at a regional scale due to varying parameters among LiDAR data acquisitions and the availability of sufficient calibration data. Here, we present a model using a 3-D convolutional neural network (CNN), a form of deep learning capable of scanning a LiDAR point cloud, combined with coincident satellite data (spectral, phenology, and disturbance history). We compared this approach to traditional modeling used for making forest predictions from LiDAR data (height metrics and random forest) and found that the CNN had consistently lower uncertainty. We then applied the CNN to public data over six New England states in the USA, generating maps of 14 forest attributes at a 10 m resolution over 85% of the region. Aboveground biomass estimates produced a root mean square error of 36 Mg ha−1 (44%) and were within the 97.5% confidence of independent county-level estimates for 33 of 38 or 86.8% of the counties examined. CNN predictions for stem density and percentage of conifer attributes were moderately successful, while predictions for detailed species groupings were less successful. The approach shows promise for improving the prediction of forest attributes from regional LiDAR data and for combining disparate LiDAR datasets into a common framework for large-scale estimation.

Elias Ayrey↗

“The Goose” Pulsar Wind Nebula of PSR J1016–5857: The Birth of a Plerion

We report the results of X-ray (CXO) and radio (ATCA) observations of the pulsar wind nebula(PWN) powered by the young pulsar PSR J1016–5857, which we dub “the Goose” PWN. In bothbands the images reveal a tail-like PWN morphology which can be attributed to pulsar’s motion. Bycomparing archival and newCXOobservations, we measure the pulsar’s proper motionμ= 28.8±7.3mas yr−1, yielding a projected pulsar velocityv≈440±110 km s−1(atd= 3.2 kpc); its direction isconsistent with the PWN shape. Radio emission from the PWN is polarized, with the magnetic fieldoriented along the pulsar tail. The radio tail connects to a larger radio structure (not seen in X-rays)which we interpret as a relic PWN (also known as a plerion). The spectral analysis of theCXOdatashows that the PWN spectrum softens from Γ = 1.7 to Γ≈2.3−2.5 with increasing distance fromthe pulsar. The softening can be attributed to the rapid synchrotron burn-off, which would explainthe lack of X-ray emission from the older relic PWN. In addition to non-thermal PWN emission, wedetected thermal emission from a hot plasma which we attribute to the host SNR. The radio PWNmorphology and the proper motion of the pulsar suggest that the reverse shock passed through thepulsar’s vicinity and pushed the PWN to one side.

Pulsars↗

NASA’s Human Data Repositories: An In Depth Look at the New Data Request Process

As NASA transitions its focus to travel back to the moon and on to new destinations, the need to ensure the capture, analysis, and application of research and medical data is of greater urgency than at any other previous time. In this era of limited resources and challenging schedules, the Human Research Program (HRP), based at NASA’s Johnson Space Center (JSC), recognizes the need to extract the greatest possible amount of information from the data already captured. To this end, the HRP Chief Scientist Office (CSO), HRP Program Planning and Control (PP&C) Office, and the Space Medicine Operations Division have been working together to make reuse of both research data and medical monitoring data more accessible to the user community through the Life Science Data Archive (LSDA) and the Lifetime Surveillance of Astronaut Health (LSAH) Repositories. The task of both LSDA and LSAH repositories is to acquire, preserve, and distribute retrospective research (LSDA) and medical (LSAH) data and information both within the NASA community and to the science community at large, for knowledge discovery, retrospective analysis, and planning of future research studies. An additional goal is to encourage collaboration with non-NASA institutions also faced with enhancing human performance in extreme environments. In September 2022, the LSDA website and its contents transitioned to a new NASA Life Sciences Portal (https://nlsp.nasa.gov/explore/lsdahome). This site continues to feature publicly releasable information such as non-attributable datasets, experiment descriptions (from Project Mercury to ISS, as well as from multiple flight analog missions), descriptions of medical monitoring data, and LSAH newsletters (1992 - 2022). The website also provides an updated portal to request additional research and medical data not accessible from the public website. This presentation will provide an in-depth look at the new system as it relates to finding and requesting retrospective data. We will also detail processes from making a request to delivering data for different types of data requests (i.e., attributable, or non-attributable). This includes descriptions of various approval boards, what information and actions the requestor is responsible for, and key milestones in making data available for reuse.

D. M. Thomas↗

Estimating Emissions of Methane Consistent with Atmospheric Measurements of Methane and δC-13 of Methane

We have constructed an atmospheric inversion framework based on TM5-4DVAR to jointly assimilate measurements of methane and δC-13 of methane in order to estimate source-specific methane emissions. Here we present global emission estimates from this framework for the period 1999–2016. We assimilate a newly constructed, multi-agency database of CH4 and δC-13 measurements. We find that traditional CH4-only atmospheric inversions are unlikely to estimate emissions consistent with atmospheric δC-13 data and assimilating δC-13 data is necessary to derive emissions consistent with both measurements. Our framework attributes ca. 85% of the post-2007 growth in atmospheric methane to microbial sources, with about half of that coming from the tropics between 23.5° N and 23.5° S. This contradicts the attribution of the recent growth in the methane budget of the Global Carbon Project (GCP). We find that the GCP attribution is only consistent with our top-down estimate in the absence of δC-13 data. We find that at global and continental scales, δC-13 data can separate microbial from fossil methane emissions much better than CH4 data alone, and at smaller scales this ability is limited by the current δC-13 measurement coverage. Finally, we find that the largest uncertainty in using δC-13 data to separate different methane source types comes from our knowledge of atmospheric chemistry, specifically the distribution of tropospheric chlorine and the isotopic discrimination of the methane sink.

Methane↗

Collective network routing

Disclosed are a unified method and apparatus to classify, route, and process injected data packets into a network so as to belong to a plurality of logical networks, each implementing a specific flow of data on top of a common physical network. The method allows to locally identify collectives of packets for local processing, such as the computation of the sum, difference, maximum, minimum, or other logical operations among the identified packet collective. Packets are injected together with a class-attribute and an opcode attribute. Network routers, employing the described method, use the packet attributes to look-up the class-specific route information from a local route table, which contains the local incoming and outgoing directions as part of the specifically implemented global data flow of the particular virtual network.

97 MATHEMATICS AND COMPUTING↗

Aggregation server for grid-integrated vehicles

Methods, systems, and apparatus for aggregating electric power flow between an electric grid and electric vehicles are disclosed. An apparatus for aggregating power flow may include a memory and a processor coupled to the memory to receive electric vehicle equipment (EVE) attributes from a plurality of EVEs, aggregate EVE attributes, predict total available capacity based on the EVE attributes, and dispatch at least a portion of the total available capacity to the grid. Power flow may be aggregated by receiving EVE operational parameters from each EVE, aggregating the received EVE operational parameters, predicting total available capacity based on the aggregated EVE operational parameters, and dispatching at least a portion of the total available capacity to the grid.

25 ENERGY STORAGE↗

Solar soft cost ontology for multi-stakeholder knowledge base

Introduction: Solar soft costs can account for 60% of the cost of an installed solar system, thus cost reductions for solar hinge on reducing soft costs. Soft costs are most frequently defined as non-hardware costs. Defining something by what it isn’t makes it inherently difficult to identify what exactly it is, which in turn makes it difficult to study. Our goal is to develop an ontology that identifies 1) a consistent and defined soft cost vocabulary, 2) who creates, shares and acquires soft cost knowledge, and 3) the learning processes used to facilitate knowledge flows. Ultimately, identifying these aspects of solar soft costs will provide a pathway for public policy and market interventions to reduce soft costs. Methods: To build the solar soft cost ontology (SSCO) we built a corpus of solar soft cost literature (through keyword search), then coded the corpus for all concepts related to or influencing costs, barriers, or time. Finally, we organized the concepts into taxonomies, including soft costs and network actors, and developed the properties (i.e., attributes and relationships) that link the concepts. In phase two, we will code a set of solar installer case studies and complimentary solar sector (e.g., distributors, software providers, trade organizations) firm case studies to update the SSCO, documenting changes and additions resulting from the use of practitioner feedback. Results and Discussion: The resulting SSCO includes concepts, attributes, and relationships that provide a rich and deep knowledge base that merges academic and practitioner expertise to create a shared and exhaustive vocabulary related to soft costs, a network of actors that impact those soft costs, and the attributes and relationships that connect them. The applications of the SSCO extend to a diverse group of stakeholders, including researchers, policy makers, and practitioners, engaged in reducing solar soft costs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

GeoRePORT Case Study Examples: Reporting Using the Geothermal Resource Portfolio Optimization and Reporting Technique (GeoRePORT): Preprint

The Geothermal Research Portfolio Optimization & Reporting Technique (GeoRePORT) was developed with funding from the United States Department of Energy's Geothermal Technologies Office (GTO) to assist in identifying and pursuing long-term investment strategies through the development of a resource reporting protocol. GeoRePORT provides scientists and non-scientists a comprehensive and quantitative means of reporting: (1) features intrinsic to geothermal sites (project grade) and, (2) maturity of the development (project readiness). Because geothermal feasibility is not determined by any single factor (e.g. temperature, permeability, permitting), a site's project grade and readiness are evaluated on twelve independent attributes pertaining to geological, technical, or socio-economic feasibility. In this paper, we present case studies illustrating how GeoRePORT can be used to compare geological, technical, and socio-economic attributes between geothermal systems. The consistent and objective assessment protocols used in GeoRePORT allow for comparison of project attributes across unique locations and geological settings. GeoRePORT case studies outline the geological, socio-economic and technical features of four individual geothermal sites: Coso, Chena, Dixie Valley, and White Sands Missile Range. The case studies presented herein illustrate the usefulness of GeoRePORT in evaluating project risk/return, identifying gaps in reported data, evaluating R&D impact, and gathering insights on successes/failures as applicable to future projects.

15 GEOTHERMAL ENERGY↗

Comprehensive analysis of technical efficiency of business establishments in Santa Barbara County: Evaluation of spatial and aspatial stochastic frontier models

One of the main objectives of land-use and transport models is to accurately describe the organization and composition of the regional economy. However, these models currently lack the integration of competitiveness and performance of the regional economy, which in-turn is dependent on performance and efficiency of business establishments in the region. In this study, we present a framework that integrates the aspects of economic efficiency of business establishments within the context of land-use and transport models. For this purpose, we comprehensively assess the impacts of both internal and external attributes of business establishment on its efficiency. In this process, we specifically focus on aspects of incorporating locational characteristics using two frameworks - (a) measuring locational attributes using link-based multiple centrality indicators (L-MCI) and (b) measuring neighborhood effects of business establishments through spatial proximity that account for co-location and competition. We make use of the stochastic frontier modeling framework to investigate the factors impacting business establishment-level output measured as sales per unit area. Specifically, the aspatial stochastic frontier (ASF) model incorporates L-MCI measures as covariates and the spatial stochastic frontier (SSF) model incorporates neighborhood effects of business establishments through network distance measured using the roadway network for Santa Barbara County.Overall, the empirical results suggest that there exist significant inefficiencies across all business establishment types that are mainly impacted by internal attributes of the business. For example, larger and older business establishments are more efficient than business establishments that are smaller in size and younger in age. Furthermore, the results also suggest that locational impacts are better captured using the ASF specification when compared with SSF specification. For instance, the spatial correlation estimate (from SSF) although statistically significant, is very weak. Thereby, indicating a lack of spatial structure in technical efficiency of businesses manifested in the form of co-location and competition. In contrast, the ASF model captures spatial structure of technical efficiency thoroughly with inclusion of the L-MCI measures. This indicates that L-MCI measures have varying levels of impact on efficiency (positive or negative) depending on its relative location in the region. For instance, retail trade businesses have higher levels of revenue (or sales per unit area) when located along links in a grid-network like structure e.g. downtown areas. Additionally, businesses in professional services have no impact on their efficiency based on the configuration and structure of the regional transportation network. However, results from both specifications indicate that there exist major benefits on efficiency of business establishments from local competition for retail trade and healthcare services.

Ravulaparthy, Srinath↗

Computer processing through distance-based quality score method in geospatial-temporal semantic graphs

A computer-implemented method of improving processing of overhead image data by a processor using a distance-based quality score in a geospatial-temporal semantic graph. An allowable range for each attribute in the subgraph search template is defined. For each match in a comparison, attribute values of each match element are compared against the preferred range and the allowable range to compute a corresponding distance of each match attribute from the subgraph search template. A corresponding overall match quality score is determined for each match from the subgraph search template, wherein determining the corresponding overall match qualities is performed using a corresponding required quality score and a corresponding optional quality score. All corresponding overall match quality scores are sorted into an ordered list and then displayed.

97 MATHEMATICS AND COMPUTING↗

GeoRePORT Case Study Examples: Reporting Using the Geothermal Resource Portfolio Optimization and Reporting Technique (GeoRePORT)

The Geothermal Research Portfolio Optimization & Reporting Technique (GeoRePORT) was developed with funding from the United States Department of Energy's Geothermal Technologies Office (GTO) to assist in identifying and pursuing long-term investment strategies through the development of a resource reporting protocol. GeoRePORT provides scientists and non-scientists a comprehensive and quantitative means of reporting: (1) features intrinsic to geothermal sites (project grade) and, (2) maturity of the development (project readiness). Because geothermal feasibility is not determined by any single factor (e.g. temperature, permeability, permitting), a site's project grade and readiness are evaluated on twelve independent attributes pertaining to geological, technical, or socio-economic feasibility. In this paper, we present case studies illustrating how GeoRePORT can be used to compare geological, technical, and socio-economic attributes between geothermal systems. The consistent and objective assessment protocols used in GeoRePORT allow for comparison of project attributes across unique locations and geological settings. GeoRePORT case studies outline the geological, socio-economic and technical features of four individual geothermal sites: Coso, Chena, Dixie Valley, and White Sands Missile Range. The case studies presented herein illustrate the usefulness of GeoRePORT in evaluating project risk/return, identifying gaps in reported data, evaluating R&D impact, and gathering insights on successes/failures as applicable to future projects.

40 EE - Geothermal Technologies Office (EE-4G)↗

Using Graph Edit Distance for Noisy Subgraph Matching of Semantic Property Graphs

The subgraph matching problem is a fundamental problem in graph theory that is known to be NP-complete. In this study, performers were asked to develop algorithms to search for semantic property graphs that were subgraphs of a large knowledge graph. The templates provided contained structural information about the subgraphs and some attributes for each node and edge. There also exists a similarity measure between a set of attribute values that occurs on every node and edge. Algorithms performed well in the case where an exact match existed, but performers were also provided templates that had noise added such that there existed no match in the knowledge graph. Performers were asked to find the closest matches to those noisy subgraphs. To evaluate performance on this task, we developed a version of the graph edit distance algorithm to measure the cost of editing the template graph so that it is isomorphic in structure and attributes to the performer submission.

Ebsch, Christopher L.↗

Savannah River Remediation Liquid Waste Operations Making the Workplace Safer - Lean and Human Performance Improvement Initiatives - 17244

The Savannah River Site, a U.S. Department of Energy facility, contracted Savannah River Remediation (SRR) to manage its liquid waste project, which is a unique, high hazard nuclear waste treatment and disposal facility consisting of 51, one million gallon underground waste tanks, a solvent extraction processing unit, a vitrification facility for the highest radioactive waste, and a grout solidification and disposal facility for a decontaminated salt solution. Our Project mission is to treat the nuclear waste and close the associated storage and treatment facilities, of which, 8 of the 51 tanks have been closed to date. Over the past three years, SRR implemented a Lean Business Management System to address site inefficiencies, aging infrastructure concerns and budget constraints. The Lean philosophy started with the work of W. Edwards Deming and his contemporaries. In more recent years the process has matured in the Toyota Production System and migrated into fields as diverse as services industries, health-care, and now the DOE complex. Like safety, continuous improvement is a fundamental core business value that starts at the top. The Lean Business System, led by our executive management team, drives quality, production and waste elimination by focusing on People using a structured Process that allows the workforce to identify and fix problems in their workplace. Many inefficiencies and quality related issues start with the desire to make systems fail-safe without defining the core requirements for which that process or program was created. This leads to added complexity and latent or inherent human performance issues embedded within our processes. While Lean can't fix all problems, a combination of strong nuclear safety culture, robust conduct of operations, active human performance improvement process, and a business practice of continuously looking for improvements leads to excellence across our industry and creates a culture that is worthy of promoting. Without strong management, our systems fail because no one sponsors or encourages those attributes we covet. Leadership starts at the top with our customer defining what provides 'value' to them, and filters down through to the organization and ultimately the workforce in day to day conduct of operations. It is imperative that our customer drives these desirable ideals through recognition and contractual requirements to encourage and support those behavioral traits that are critical to our ongoing success.This paper focuses on how the Lean Business Management System supports those attributes that we value: a strong nuclear safety culture; disciplined conduct of operations; and a culture of robust human performance and continuous improvement. These attributes in our daily work environment propel a safer, more consistent, more efficient workplace. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Anomaly detection for cyber-physical systems

An anomaly detector is configured to construct cyber and/or physical features comprising information configured to characterize the cyber and/or physical state of a cyber-physical system. The physical features may be based on physical and/or physics-based relationships between a plurality of physical state attributes. A health of the cyber-physical system may be based on an error between estimates of one or more of the physical state attributes and measurements of the one or more physical state attributes. The relationships may be incorporated into machine learning membership functions used to classify cyber and/or physical behavior of the system.

Rieger, Craig G.↗

Are the U.S. Biorefineries Over the Hurdle of 2000 Ton Daily Throughput Yet?

The efficient utilization of lignocellulosic biomass for biofuel and biochemical production is hindered by material handling issues such as clogging and segregation among other challenges. Preprocessing methods such as drying, screening, and milling have improved conversion yield but have not sufficiently enhanced flowability, especially herbaceous biomass. The poor flowability of herbaceous biomass is rooted in some particle attributes that remain less altered by those methods, e.g., irregular particle shape, high roughness, and high compressibility, making it hard to scale up throughput to a key benchmark for a biorefinery – 2000 ton per day. Applying additional preprocessing methods like pelletization and torrefaction to drastically change those particle attributes can improve flow and handling but has not been comprehensively verified through test. The flowability of herbaceous biomass feedstock formats generated by three different preprocessing methods was recently assessed at Idaho National Laboratory’s Biomass Feedstock National User Facility: first, loose particles size reduced from as-received materials; second, pellets produced from an efficient densification process; and third, powders milled from torrefied pellets. Benchmarking tests including static angle of repose, basic flow energy measured in a powder rheometer, and discharge flow in an adjustable hopper, were conducted to evaluate those feedstock formats. Beyond the capacity of existing experimental apparatuses, a digital engineering approach involving flow simulations and AI models were used to identity the material attributes and processing parameters that have dominant influences on flow throughput. Techno-economic analysis focusing on hopper flow as a typical material handling operation was conducted for those feedstock formats. Perspectives will be discussed on whether the 2000-ton daily throughput for a biorefinery is achievable at an acceptable cost by using any of the tested preprocessing methods.

09 - BIOMASS FUELS↗

The Effect of Air Separations on Fast Pyrolysis Products for Forest Residue Feedstocks

This study investigates the intricate relationship between biomass preprocessing and pyrolysis product yields, employing the air classification technique for the treatment of loblolly pine residues with varying moisture content. A comprehensive exploration of the physicochemical properties of air-classified loblolly pine informs a sophisticated pyrolysis simulation model. Given the complex and multifaceted nature of biomass pyrolysis, operating across diverse temporal and spatial scales, a pyrolysis kinetics-based CFD–DEM simulation method is employed to predict product yields. Results showed that the elevated moisture content amplifies particle adhesiveness, necessitating augmented air velocities for effective separation, thereby influencing the efficiency of the separation process. While carbon and hydrogen contents exhibit relative stability across diverse moisture contents and blower frequencies, the oxygen content undergoes noticeable changes. For example, the oxygen contents were measured as 29.2 and 38.6 wt% in the light fraction of 30% moisture content sample at blower frequencies of 10 and 20 Hz, respectively. An intriguing finding emerges from pyrolysis simulation, indicating that a lower blower frequency in air classification moderately enhances bio-oil yield and significantly improves its quality, particularly in terms of water content. For instance, the water content in the bio-oil was about 1.5% and 10% in the heavy and light fractions, respectively from 10% moisture sample under 15 Hz blower frequency. In summary, a detailed understanding and strategic manipulation of critical material attributes in biomass through efficient fractionation techniques are imperative for advancing fast pyrolysis as a sustainable avenue for renewable energy and chemical production.

09 BIOMASS FUELS↗