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At least 271 records · Page 15

Big Data Synchrophasor Monitoring and Analytics for Resiliency Tracking (BDSMART)

This report contains key findings from a project titled Big Data Synchrophasor Monitoring and Analytics for Resiliency Tracking (BDSMART), which was carried out through a collaborative effort of a team of researchers from Texas A&M Engineering Experiment Station, Temple University, and Quanta Technology, LLC. The in-kind support came from OSIsoft (acquired by AVEVA), which provided their PI Historian software to demonstrate the use case of streaming PMU data. The first section of the report describes the project goals and objectives related to the development of Machine Learning (ML) models capable of detecting and classifying events by processing phasor measurements captured in the field by Phasor Measurement Units (PMUs). The data for this study was contributed by the utilities/ISOs from the Western and Eastern interconnects and ERCOT, further referred to as Interconnect B (IC B), Interconnect A (IC A), and Interconnect C (IC C), respectively. The approach that the BDSMART Research Team proposed and the key research tasks defined by the team are outlined in this section. The next section describes the technical approach. We first discuss the data constraints related to the PMU measurements and data interpretation constraints imposed by the data contributors. They provided neither the topological information of the grid nor PMU placement locations and captured recorded data at very few locations in the system with the reporting rate of either 30 or 60 fps. The recordings are mostly positive sequence voltage, frequency, and ROCOF, and in some limited cases, three-phase voltages and currents. We then reflect on the bad data issues that stem from poor recording practices and vague definitions of the PMU status bits to supposedly be used for bad data identification. Finally, the data discovery points to imprecise time stamps with incomplete event start/end time, as well as inconsistent and incomplete event labeling, which combined make the implementation of the data models using supervising learning quite challenging. Following the data discovery study, we hypothesize that because the IC B data has the most complete labels, we should focus our model development on that data and then test it on data from other interconnects. We also define the common metrics used to evaluate the results from the ML algorithm tests. We concluded this section by summarizing the common ML models we used and explaining how we implemented and tested them. The issues from this section are expanded in the Training Dataset Report from this project. The final section of this report deals with the accomplishments and conclusions. As the accomplishments, we formulate the problem we are solving and what is achieved by solving the problem. We then reflect on each of the analytics tools we developed and point out the performance of each tool when applied to solving the mentioned problems. We reference this work for further details to the papers we published on each tool. In the conclusions, we give recommendations on how to improve future PMU recording practices to facilitate the ML algorithm implementation and guidance for the future standardization work aimed at clarifying the ambiguities associated with the PMU status bits. We finally list future tasks that can bring about further improvements in the proposed algorithms. The issues from this section are expanded in the Training, and Test Dataset Report filed at the project completion date.

97 MATHEMATICS AND COMPUTING↗

Development and Bench-Scale Testing of a Novel Biphasic Solvent-Enabled Absorption Process for Post-Combustion Carbon Capture (Final Technical Report)

A new class of biphasic solvents was developed, and the concept of the enabled carbon dioxide (CO 2 ) absorption process was tested for post-combustion carbon capture in our previous lab-scale research. The primary goals of this project were to advance the development of the novel biphasic CO 2 absorption process (BiCAP) and validate its technical advantages by testing the integrated technology at a 40 kWe bench-scale with actual coal-derived flue gas in a power plant environment. The project was led by the University of Illinois at Urban-Champaign (UIUC), and Trimeric Corporation served as a sub-awardee providing support in basic design and techno-economic studies. To achieve the project goals and objectives, solvent management studies, process modeling and optimization, bench-scale equipment design, construction and testing, and technical, economic and environmental assessments have been conducted. The two top-performing biphasic solvents developed in our previous research were used in this project. Biphasic solvent emissions and control were investigated in the laboratory. The emissions of the biphasic solvents from the absorber were comparable to or lower than the reference 30 wt% monoethanolamine (MEA) solution, while they could be more effectively removed in the water wash column. Lab-scale testing of solvent degradation reclamation has revealed that vacuum distillation was feasible for biphasic solvent reclamation. Aspen Plus models were used to optimize the BiCAP, and a CO 2 stripping configuration introducing a secondary cold solvent feed to the stripper was identified to be the most energy efficient. A 40 kWe bench-scale, integrated BiCAP system was successfully designed, fabricated, and installed at the UIUC’s Abbott Power Plant. Parametric testing with synthetic flue gas has demonstrated that the two biphasic solvents required a more than 40% lower heat duty for CO 2 desorption as compared to the reference MEA tested on the same bench-scale skid. Slipstream testing with actual coal flue gas for a total of 31 days in two test campaigns has further demonstrated stable operation of the bench-scale skid. During the first campaign targeting 90% CO 2 removal, the heat duty averaged at 2,183 MJ/tonne of CO 2 captured and during the second campaign targeting 95% removal, the heat duty averaged at 2,450 MJ/tonne of CO 2 captured. A techno-economic analysis has revealed that for integration of the BiCAP into a 650-MWe pulverized coal-fired power plant, the parasitic power loss was reduced by ~20%, and the cost of CO 2 capture was reduced by ~21% ($36.3/tonne on a December 2018 dollar basis) compared to the U.S. Department of Energy (DOE)’s baseline Case B12B. As progression from this bench-scale development effort, a new project “Engineering-Scale Testing of the Biphasic Solvent Based CO 2 Absorption Capture Technology at a Covanta Waste-to-Energy Facility” was awarded by the DOE, launched in February 2023, to allow the team to further test the technology and demonstrate its technical and economic advantages at a pilot scale.

20 FOSSIL-FUELED POWER PLANTS↗

Supplement to M&V Guidelines: Measurement and Verification for Performance-Based Contracts Version 4.0

Measurement and verification (M&V) are key to determining and confirming the continued operation of, and savings associated with, performance-based contracts. The Federal Energy Management Program (FEMP) updates these guidelines to reflect the evolution of M&V to incorporate industry best practices and ensure that savings from these performance-based projects are properly planned, communicated, and realized. FEMP released M&V Guidelines: Measurement and Verification for Federal Energy Projects Version 3.0 in 2008. This document was developed with input from industry-government working groups, previous M&V guideline authors, and national laboratory subject matter experts. The document provided the methods and guidelines, with a focus on federal energy savings performance contracts (ESPCs). When FEMP released M&V Guidelines: Measurement and Verification for Performance-Based Contracts Version 4.0 in 2015, FEMP expanded the intended audience to include anyone (energy managers, procurement officers, and contractors) involved in implementing performance-based contracts. The streamlined M&V Guidelines Version 4.0 provided the procedures and guidelines needed to quantify savings resulting from installing energy-efficient equipment, water conservation, improved operation and maintenance (O&M), renewable energy, and cogeneration projects with a performance-based contract; however, it removed some of the associated details on topics such as developing regression models and sampling plans. The details and information provided in M&V Guidelines v. 3.0 are still pertinent to M&V for performance-based contracts. The objective is to keep FEMP M&V version 4.0 condensed, providing the reference document for specifying M&V methods and procedures and a resource for developing project-specific M&V plans; this supplement provides additional details. The content of this supplement has been updated to include pertinent revisions between M&V version 3.0 and M&V version 4.0 by providing details and updating the content to ensure relevancy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Machine Learning the Voltage of Electrode Materials in Metal-Ion Batteries

Machine-learning (ML) techniques have rapidly found applications in many domains of materials chemistry and physics where large data sets are available. Aiming to accelerate the discovery of materials for battery applications, in this work, we develop a tool based on ML models to predict voltages of electrode materials for metal-ion batteries. To this end, we use deep neural network, support vector machine, and kernel ridge regression as ML algorithms in combination with data taken from the Materials Project database, as well as feature vectors from properties of chemical compounds and elemental properties of their constituents. We show that our ML models have predictive capabilities for different reference test sets and, as an example, we utilize them to generate a voltage profile diagram and compare it to density functional theory calculations. In addition, using our models, we propose nearly 5000 candidate electrode materials for Na- and K-ion batteries. We also make available a web-accessible tool that, within a minute, can be used to estimate the voltage of any bulk electrode material for a number of metal ions. Here, these results show that ML is a promising alternative for computationally demanding calculations as a first screening tool of novel materials for battery applications.

25 ENERGY STORAGE↗

Advanced Controls for the Multi-pod Centipod WEC device

Dehlsen Associates, LLC (DA) has developed a Wave Energy Converter (WEC), Centipod, which is a multiple point absorber, extracting wave energy primarily in the heave direction through a plurality of point absorber floats sharing a common stable reference structure. The objective of this project was to develop advanced control algorithms that will be used to reduce Levelized Cost of Energy (LCOE). This project investigated the use of Model Predictive Control (MPC) to improve the power capture of the WEC. The MPC controller developed in this work is a state-space, “look ahead” controller approach using knowledge of past and current states to predict future states to take action with the PTO to maximize power capture while still respecting system constraints. In order to maximize power, which is the product of force and velocity, the controller must aim to create phase alignment between excitation force and velocity. This project showed a 161% improvement in the Annual Energy Production (AEP) for the Centipod WEC when utilizing MPC, compared to a baseline, fixed passive damping control strategy. This improvement in AEP was shown to provide a substantial benefit to the WEC’s overall Cost of Energy, reducing LCOE by 50% from baseline. The results of this work proved great potential for the adoption of Model Predictive Controls in Wave Energy Converters.

16 TIDAL AND WAVE POWER↗

Mu2e: Modeling Drift of Ionized Particles with ML

The Mu2e experiment searches for charged lepton flavor violation through muon-to-electron conversion in the field of a nucleus. The signal is a monoenergetic electron with an energy of 104.97 MeV. Its momentum is reconstructed using information from drifting ionized particles in a straw tracker detector. This project analyzes the drift of ionized particles with a deep neural network to help improve the momentum reconstruction process. The model yields a 20% improvement in resolution from a reference linear model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Stability and instability of thermocapillary convection in models of the float-zone crystal-growth process

This project was concerned with the determination of conditions of guaranteed stability and instability for thermocapillary convection in a model of the float-zone crystal-growth process. This model, referred to as the half-zone, was studied extensively, both experimentally and theoretically. Our own earlier research determined, using energy-stability theory, sufficient conditions for stability to axisymmetric disturbances. Nearly all results computed were for the case of a liquid with Prandtl Number Pr = 1. Attempts to compute cases for higher Prandtl numbers to allow comparison with the experimental results of other researchers were unsuccessful, but indicated that the condition guaranteeing stability against axisymmetric disturbances would be a value of the Marangoni number (Ma), significantly higher than that at which oscillatory convection was observed experimentally. Thus, additional results were needed to round out the stability picture for this model problem. The research performed under this grant consisted of the following: (1) computation of energy-stability limits for non-axisymmetric disturbances; (2) computation of linear-stability limits for axisymmetric and non-axisymmetric disturbances; (3) numerical simulation of the basic state for half- and full-zones with a deformable free surface; and (4) incorporation of radiation heat transfer into a model energy-stability problem. Each of these is summarized briefly below.

Neitzel, G. P.↗

Mu2e: Modeling Drift of Ionized Particles with ML

The Mu2e experiment searches for charged lepton flavor violation through muon-to-electron conversion in the field of a nucleus. The signal is a monoenergetic electron with an energy of 104.97 MeV. Its momentum is reconstructed using information from drifting ionized particles in a straw tracker detector. This project analyzes the drift of ionized particles with a deep neural network to help improve the momentum reconstruction process. The model yields a 20% improvement in resolution from a reference linear model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Impacts of rising air temperatures and emissions mitigation on electricity demand and supply in the United States: a multi-model comparison

The electric power sector both affects and is affected by climate change. Numerous studies highlight the potential of the power sector to reduce greenhouse gas emissions. Yet fewer studies have explored the physical impacts of climate change on the power sector. The present analysis examines how projected rising temperatures affect the demand for and supply of electricity. We apply a common set of temperature projections to three well-known electric sector models in the United States: the US version of the Global Change Assessment Model (GCAM-USA), the Regional Electricity Deployment System model (ReEDS), and the Integrated Planning Model (IPM®). Incorporating the effects of rising temperatures from a control scenario without emission mitigation into the models raises electricity demand by 1.6 to 6.5 % in 2050 with similar changes in emissions. The increase in system costs in the reference scenario to meet this additional demand is comparable to the change in system costs associated with decreasing power sector emissions by approximately 50 % in 2050. This result underscores the importance of adequately incorporating the effects of long-run temperature change in climate policy analysis.

McFarland, James↗

Promoting A-Priori Interoperability of HLA-Based Simulations in the Space Domain: The SISO Space Reference FOM Initiative

Distributed and Real-Time Simulation plays a key-role in the Space domain being exploited for missions and systems analysis and engineering as well as for crew training and operational support. One of the most popular standards is the 1516-2010 IEEE Standard for Modeling and Simulation (M&S) High Level Architecture (HLA). HLA supports the implementation of distributed simulations (called Federations) in which a set of simulation entities (called Federates) can interact using a Run-Time Infrastructure (RTI). In a given Federation, a Federate can publish and/or subscribes objects and interactions on the RTI only in accordance with their structures as defined in a FOM (Federation Object Model). Currently, the Space domain is characterized by a set of incompatible FOMs that, although meet the specific needs of different organizations and projects, increases the long-term cost for interoperability. In this context, the availability of a reference FOM for the Space domain will enable the development of interoperable HLA-based simulators for related joint projects and collaborations among worldwide organizations involved in the Space domain (e.g. NASA, ESA, Roscosmos, and JAXA). The paper presents a first set of results achieved by a SISO standardization effort that aims at providing a Space Reference FOM for international collaboration on Space systems simulations.

Moller, Bjorn↗

Autonomous Navigation with Ground-to-Space Doppler Measurements Referenced to a Temperature-Compensated Crystal Oscillator

The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) has spent several years developing operational Onboard Navigation Systems (ONS's) to provide real-time autonomous, high-accuracy navigation products for spacecraft using NASA's space and ground communication systems. The highly successful Tracking and Data Relay Satellite System (TDRSS) ONS (TONS) experiment on the Explorer Platform/Extreme Ultraviolet Explorer (EP/EUVE) spacecraft, launched June 7, 1992, flight-demonstrated the ONS for high-accuracy navigation using TDRSS forward- link communications services, In late 1994, the ground station ONS (GONS) experiment, using the same EP/EUVE flight hardware, flight-demonstrated the feasibility of high-accuracy autonomous navigation using ground station forward-link communication services, with an ultrastable oscillator (USO) as the frequency reference (1 part in 10(exp 10) over 24 hours). This paper provides a follow-on analysis of GONS performance to assess the navigation accuracy achievable if GONS uses the significantly less stable (5 parts in 10(exp 8) over 24 hours, compared with a specification of 1 part in 10(exp 6)) Temperature-Compensated Crystal Oscillator (TCXO), which is integral to the transponder, as a frequency reference rather than an external USO. The GONS TCXO experiment results from a 20-day period are used to project the expected performance of an operational system. The GONS processes Doppler data derived from nominally scheduled ground station forward-link communication services using a sequential estimation algorithm enhanced by a sophisticated process noise model to provide onboard orbit and frequency determination. To evaluate the navigation accuracies achievable if a TCXO were used, actual experiment data (which used the USO as the frequency reference) were corrupted with errors from real TDRSS one-way return tracking measurements taken from EP/EUVE's TCXO. Analysis of the GONS TCXO experiment performance indicates that real-time onboard position accuracies of better than 300 meters (1 sigma) are achievable with as few as two tracking contacts per day for the EP/EUVE 525-kilometer altitude, 28.5-degree inclination orbit, provided the TCXO is as stable as that in EP/EUVE's TDRSS transponder. GONS using a TCXO frequency reference provides a viable option for many upcoming spacecraft missions with moderate position accuracy requirements and an interest in reducing their operational costs with autonomous navigation.

Radomski, M. S.↗

Predicting Damages to Remainder Parcels in Right-of-Way Acquisitions for Expanding Transportation Infrastructure: Using a Truncated Finite-Mixture Model

Right-of-way acquisition is a critical component of transportation infrastructure development. Transportation infrastructure projects cannot proceed without proper right-of-way acquisition or may face significant delays. State Departments of Transportation frequently acquire parcels of land for roadway expansion projects. A majority of these acquisitions can be partial takings, referring to a portion of a parcel that is acquired. The remainder of the property usually suffers economic changes due to the partial acquisition, which can be calculated as damage percentages. The damage percentage represents the extent to which the remaining land or property value has been diminished due to the acquisition. It reflects the remaining property value percentage that may have been lost or compromised due to the acquisition. Here, this study aims to provide a robust model to estimate damage percentages to the remainder parcels that may help state Departments of Transportation appraisers make early predictions about the damages in cases involving partial takings. The research uses 509 appraisal reports from the Tennessee Department of Transportation to identify the key parcel attributes that influence the percentage of damages. Three regression models are developed: a linear regression model, a finite-mixture model (FMM), and a truncated FMM with two latent classes. The modeling results show that the truncated FMM with two classes outperforms the other models. To validate the models, actual sales data is collected and analyzed for 59 properties, and the results suggest that the model predictions are fairly accurate. A predictive tool is developed based on the models to help appraisers anticipate right-of-way damages under different scenarios and can provide early predictions about the damages.

42 ENGINEERING↗

ARM Data-Oriented Metrics and Diagnostics Package for Climate Model Evaluation

A Python-based metrics and diagnostics package is currently being developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Infrastructure Team at Lawrence Livermore National Laboratory (LLNL) to facilitate the use of long-term, high-frequency measurements from the ARM Facility in evaluating the regional climate simulation of clouds, radiation, and precipitation. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The Coupled Model Intercomparison Project (CMIP) model data sets are also included in the package to enable model intercomparison as demonstrated in Zhang et al. (2017). The mean of the CMIP model can serve as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, and radiative fluxes, with plan to extend to more fields, such as aerosol and microphysics properties. Process-oriented diagnostics focusing on individual cloud- and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. The version 1.0 package is designed based on data collected at ARM’s Southern Great Plains (SGP) Research Facility, with the plan to extend to other ARM sites. The metrics and diagnostics package is currently built upon standard Python libraries and additional Python packages developed by DOE (such as CDMS and CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first present the input data, which constitutes the core content of the metrics and diagnostics package in section 2, and a user's guide documenting the workflow/structure of the version 1.0 codes, and including step-by-step instruction for running the package in section 3.

54 ENVIRONMENTAL SCIENCES↗

Eastern Interconnection Wide-Area Oscillation Assessment and Study Report

To meet the government mandates such as Renewable Portfolio Standards (RPS), conventional synchronous generators with rotating mass are being displaced by inverter-based resources (IBRs), leading to high penetration of renewable energy sources (RES). As a result, the inherent properties and characteristics of the transformed generation mix may significantly impact the grid behaviour, and it is of paramount significance that the impact and the consequences of the resource mix change is thoroughly understood to adopt measures to maintain reliable grid operations. Of great concern is the inter-area low-frequency oscillation, which usually propagates through a large region and has a system-wide impact. Such oscillations may lead to unnecessary or inadvertent tripping of generators, that may be simply reacting to the oscillation originating from geographically remote sites. Such tripping of generators can lead to cascading outages, system split and load loss events. Over the years, several system-wide oscillation events have been observed across all three North American interconnections. This project titled Wide-area Oscillation Assessment and Trending Study, sponsored by the Office of Electricity (OE) of the Department of Energy (DOE), aims to conduct the required research to capture and investigate the potential changes in wide-area oscillatory performance of the system as a result of resource mix transition. The Pacific Northwest National Laboratory (PNNL) conducted this research and technical staff of Federal Energy Regulatory Commission (FERC) served as advisors to the project. The primary objective of this study is to assess whether there are significant trends in the power system wide-area oscillatory behaviours, as a result of the generation-mix changes due to the increased penetration of RES in the U.S. Eastern Interconnection (EI). The analysis presented in this report can serve as reference for future grid planning and operation of the EI system. This research conducted in this project evaluates the wide-area oscillatory behaviour of the EI, using a model-based approach for potential future resource mixes, and the measurement-based analysis with 21-month phasor measurement unit (PMU) time series. The oscillation modes in EI system along with the impact of the changes of the generation mix on the frequency and damping ratio (DR) of the oscillations have been studied.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Satellite ground-terminal user simulation

Realistic simulation of satellite communication systems and evaluation of satellite networking schemes require emulation of the systems's users. A laboratory model of a Ka-band satellite-switched time-division multiple-access (SS-TDMA) communication network, referred to as the System Integration, Test, and Evaluation (SITE) project, uses special bit-error-rate (BER) test sets to simulate the transmitting and receiving users of a communication network. The bit-error-rate test sets contain circuit boards that can be modified to create a variety of interfaces to satellite system ground terminals.

Shalkhauser, Mary Jo W.↗

Camera Calibration and Alignment Metrology at Johnson Space Center’s Electro-Optics Laboratory

It is increasingly common to see spacecraft equipped with cameras for the purpose of navigation. Images are either sent to Earth or processed autonomously on-board to provide information about the vehicle’s position, velocity, and/or attitude. These can be images of stars or celestial bodies for absolute navigation, or images of another spacecraft for relative navigation. While monocular cameras do not provide range information, the images they capture can be processed to determine bearing vectors to target objects within the camera’s field of view. For a camera to be effective in navigation, it must be carefully calibrated and aligned. This involves accurately modeling the optical effects that govern the projection of line-of-sight directions onto the camera’s pixels and determining the camera’s orientation relative to the spacecraft’s reference frame. Engineers at Johnson Space Center’s Electro-Optics Lab regularly perform camera inspection, calibration, and alignment metrology. This was done for the Orion Optical Navigation (OpNav) Camera, the Orion Docking Camera (DCAM), and for numerous cameras belonging to commercial partners. The nature of optical navigation means that cameras must be well-calibrated and their attitude well understood to provide high accuracy bearing measurements to the navigation filter. The stringent accuracy requirements for Orion could not have been met using traditional checkerboard camera calibration or by simply relying on design drawings. This paper details the hardware, software, techniques, and algorithms used by the EOL team to achieve this level of accuracy.

Paul D Mckee↗

Camera Calibration and Alignment Metrology at Johnson Space Center’s Electro-Optics Laboratory

It is increasingly common to see spacecraft equipped with cameras for the purpose of navigation. Images are either sent to Earth or processed autonomously on-board to provide information about the vehicle’s position, velocity, and/or attitude. These can be images of stars or celestial bodies for absolute navigation, or images of another spacecraft for relative navigation. While monocular cameras do not provide range information, the images they capture can be processed to determine bearing vectors to target objects within the camera’s field of view. For a camera to be effective in navigation, it must be carefully calibrated and aligned. This involves accurately modeling the optical effects that govern the projection of line-of-sight directions onto the camera’s pixels and determining the camera’s orientation relative to the spacecraft’s reference frame. Engineers at Johnson Space Center’s Electro-Optics Lab regularly perform camera inspection, calibration, and alignment metrology. This was done for the Orion Optical Navigation (OpNav) Camera, the Orion Docking Camera (DCAM), and for numerous cameras belonging to commercial partners. The nature of optical navigation means that cameras must be well-calibrated and their attitude well understood to provide high accuracy bearing measurements to the navigation filter. The stringent accuracy requirements for Orion could not have been met using traditional checkerboard camera calibration or by simply relying on design drawings. This paper details the hardware, software, techniques, and algorithms used by the EOL team to achieve this level of accuracy.

Paul McKee↗

Measurements and Prediction of Sooting Tendencies of Pure Hydrocarbons

The amount of soot formed in combustion devices such as engines depends strongly on the chemical structure of the fuel. Over the past 10 years we have measured quantitative sooting tendencies for hundreds of pure hydrocarbons representative of those in practical fuels. The sooting tendencies have been characterized in terms of Yield Sooting Index (YSI), which is based on the amount of soot formed in a methane/air reference flame when a small amount of the test compound is doped into the fuel. In this new collaborative project we are developing a Quantitative Structure-Activity Relationship (QSAR) model from these results; this model can be used to predict YSI for new hydrocarbons of interest and to understand the details of the underlying chemistry. The model uses molecular descriptors to describe the structure of each compound in the database, and it predicts YSI with a feed-forward artificial neural network trained with the measured values. It has a rigorously defined applicability domain and its performance has been tested by both internal and external validation. New measurements have been performed to extend the applicability domain towards advanced biofuels and for external validation.

30 DIRECT ENERGY CONVERSION↗