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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.

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At least 451 records · Page 25

GRB 221009A: Discovery of an Exceptionally Rare Nearby and Energetic Gamma-Ray Burst

We report the discovery of the unusually bright long-duration gamma-ray burst (GRB), GRB 221009A, as observed by the Neil Gehrels Swift Observatory (Swift), Monitor of All-sky X-ray Image, and Neutron Star Interior Composition Explorer Mission. This energetic GRB was located relatively nearby (z = 0.151), allowing for sustained observations of the afterglow. The large X-ray luminosity and low Galactic latitude (b = 4$^°_.$3) make GRB 221009A a powerful probe of dust in the Milky Way. Using echo tomography, we map the line-of-sight dust distribution and find evidence for significant column densities at large distances (≳10 kpc). We present analysis of the light curves and spectra at X-ray and UV–optical wavelengths, and find that the X-ray afterglow of GRB 221009A is more than an order of magnitude brighter at T 0 + 4.5 ks than that from any previous GRB observed by Swift. In its rest frame, GRB 221009A is at the high end of the afterglow luminosity distribution, but not uniquely so. In a simulation of randomly generated bursts, only 1 in 10 4 long GRBs were as energetic as GRB 221009A; such a large E γ,iso implies a narrow jet structure, but the afterglow light curve is inconsistent with simple top-hat jet models. Using the sample of Swift GRBs with redshifts, we estimate that GRBs as energetic and nearby as GRB 221009A occur at a rate of ≲1 per 1000 yr—making this a truly remarkable opportunity unlikely to be repeated in our lifetime.

79 ASTRONOMY AND ASTROPHYSICS↗

Fuel Effects on Advanced Compression Ignition Load Limits

In order to increase the efficiency of light-duty gasoline engines, the Co-Optimization of Fuels and Engines (Co-Optima) initiative from the U.S. Department of Energy is investigating multi-mode combustion strategies. Multi-mode combustion can be describe as using conventional spark-ignited combustion at high loads, and at the part-load operating conditions, various advanced compression ignition (ACI) strategies are being investigated to increase efficiency. Of particular interest to the Co-Optima initiative is the extent to which optimal fuel properties and compositions can enable higher efficiency ACI combustion over larger portions of the operating map. Extending the speed-load range of these ACI modes can enable greater part-load efficiency improvements for multi-mode combustion strategies. In this manuscript, we investigate fuel effects for six different fuels, including four with a research octane number (RON) of 98 and differing fuel chemistries, iso-octane, and a market representative E10 fuel, on the load limits for two different ACI strategies: spark-assisted compression ignition (SACI) and partial fuel stratification-gasoline compression ignition (PFS-GCI) operation. Experimental results show that limits to intake boosting limit high load operation for most fuels, but high smoke emissions for high particulate matter index (PMI) fuels under SACI conditions could also be a limitation. Contrastingly, low load is limited by combustion efficiency, but these effects have more pronounced variation with fuel chemistry for PFS-GCI than with SACI. Additional, distinct effects affecting autoignition timing and peak heat release at higher speeds were identified for fuels having different low temperature heat release (LTHR) propensities for both ACI modes.

33 ADVANCED PROPULSION SYSTEMS↗

Whole-soil warming decreases abundance and modifies the community structure of microorganisms in the subsoil but not in surface soil

Abstract. The microbial community composition in subsoils remains understudied, and it is largely unknown whether subsoil microorganisms show a similar response to global warming as microorganisms at the soil surface do. Since microorganisms are the key drivers of soil organic carbon decomposition, this knowledge gap causes uncertainty in the predictions of future carbon cycling in the subsoil carbon pool (> 50 % of the soil organic carbon stocks are below 30 cm soil depth). In the Blodgett Forest field warming experiment (California, USA) we investigated how +4 ∘C warming in the whole-soil profile to 100 cm soil depth for 4.5 years has affected the abundance and community structure of microorganisms. We used proxies for bulk microbial biomass carbon (MBC) and functional microbial groups based on lipid biomarkers, such as phospholipid fatty acids (PLFAs) and branched glycerol dialkyl glycerol tetraethers (brGDGTs). With depth, the microbial biomass decreased and the community composition changed. Our results show that the concentration of PLFAs decreased with warming in the subsoil (below 30 cm) by 28 % but was not affected in the topsoil. Phospholipid fatty acid concentrations changed in concert with soil organic carbon. The microbial community response to warming was depth dependent. The relative abundance of Actinobacteria increased in warmed subsoil, and Gram+ bacteria in subsoils adapted their cell membrane structure to warming-induced stress, as indicated by the ratio of anteiso to iso branched PLFAs. Our results show for the first time that subsoil microorganisms can be more affected by warming compared to topsoil microorganisms. These microbial responses could be explained by the observed decrease in subsoil organic carbon concentrations in the warmed plots. A decrease in microbial abundance in warmed subsoils might reduce the magnitude of the respiration response over time. The shift in the subsoil microbial community towards more Actinobacteria might disproportionately enhance the degradation of previously stable subsoil carbon, as this group is able to metabolize complex carbon sources.

54 ENVIRONMENTAL SCIENCES↗

Reductions in wind farm main bearing rating lives resulting from wake impingement

This paper studies the impacts of wake impingement on main bearing rating lives predicted during the wind turbine design stage. A computational tool chain was developed to explore and quantify these effects across a wind farm populated by 10 MW wind turbines. Wind field and turbine load modelling was undertaken using the Dynamiks Python package, including application of a dynamic wake meandering model. The ISO 281 basic bearing rating life formulation was subsequently applied in order to evaluate impacts from wake effects. Analyses included a two-turbine parametric analysis, followed by a full wind farm analysis undertaken for the TotalControl 32-turbine reference wind farm, including full wind rose simulations across all operational wind speeds. Site conditions were accounted for using a Weibull wind speed distribution and a range of parametric wind direction rose models. Results indicate that wind farm main bearing rating lives are negatively impacted by the effects of wake impingement, resulting in rating life reductions for the analysed wind farm of the order of 16 % on average and as much as 20 %–25 %, both for the locating main bearing. Despite these high sensitivities, it is important to note that these resultant rating lives (i.e. the predicted lives) still far exceed the standard wind turbine operational lifetimes of 20–30 years. Wake impacts were also found to be asymmetrically related to the side on which the rotor is impinged, suggesting that, for the main bearing, there may be a “better” side for wake impingement to occur. Rating life sensitivities to wind rose shape were also observed. While these findings must be interpreted with due consideration for the various methodological limitations present, they provide compelling evidence that wake effects at the wind farm level should necessarily be included when undertaking main bearing operational load modelling, rating life assessment, or other load-related analyses.

17 WIND ENERGY↗

Water vapor isotopic composition during TRACER IOP

The TRACER-Iso project took place from June 1 to September 30, 2022 as part of the intensive observation period (IOP) of the Tracking Aerosol Convection Interactions (TRACER) project at the main project site at the La Porte, Texas, municipal airport. The project sought to use measurements of the stable isotopic composition of water vapor to better understand cloud-aerosol interactions in deep convection in a polluted urban setting. Water vapor isotopologue and humidity measurements were determined using a Picarro L2130 Water Vapor Isotope Analyzer. The instrument was deployed in the guest van and consists of three main components: a water vapor isotope analyzer, and a Los Gatos Research Water Vapor Isotope Standard Source (WVISS), and a Los Gatos Research Dry Air Source. Ambient air samples were collected through an inlet located about one meter above roof of the shipping container. Samples were then delivered to the analyzer through teflon tubing by use of an external pump to minimize the transport time between the inlet and analyzer. The inlet tubing was surrounded by a Briskheat heat trace and insulating material to ensure ambient air samples did not fall below the dew point and result in condensation. The analyzer uses cavity ringdown spectroscopy to report isotopic ratios of ambient air samples at a frequency of 1 Hz. The calibration unit of the instrument was used in conjunction with the dry air source to periodically measure the δ values of standard waters. It uses a nebulizer to push small water droplets into a hot chamber that vaporizes the water without fractionation. This vapor was then transported to the analyzer using a built-in compressor and the dry air source, which allows each standard with known δ values to be measured at a wide range of humidity values for post-measurement calibration of ambient air samples. There are multiple sources of uncertainty introduced at different stages during the data collection and processing. These include (1) instrument precision, (2) uncertainty in the secondary standards, (3) humidity-correction uncertainty, and (4) VSMOW-SLAP calibration uncertainty. Uncertainty from each step is propagated in quadrature to calculate a total uncertainty of each isotopologue. Uncertainty was determined to be 2.3‰ for δD and 0.4‰ for δ18O.

54 ENVIRONMENTAL SCIENCES↗

Inputs to GCAM-USA: IM3 Phase 2 Experiments

Overview This dataset contains XML input files for the IM3 Phase 2 version of GCAM-USA. The files are organized into two categories: Scenario-specific inputs represent hydroclimate and socioeconomic effects on water availability, heating and cooling degree-hours, and agricultural productivity. They support eight IM3 canonical scenarios: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 Model-improvement inputs extend GCAM-USA v5.3 with updated representations of coal and nuclear power plant retirements, electricity trade among U.S. interconnections, offshore carbon storage costs, and groundwater depletion constraints. Data structure Scenario-specific inputs rcp45_runoff/ and rcp85_runoff/XML files describing water availability by HUC2 basin under the RCP 4.5 and RCP 8.5 scenarios. rcp45_hdcd/ and rcp85_hdcd/XML files containing monthly-day and monthly-night heating and cooling degree-hours at the U.S. state level for different RCP-SSP combinations. rcp45_agyields/ and rcp85_agyields/XML files describing changes in agricultural productivity at the intersection of GCAM regions and HUC2 water basins for different RCP-SSP combinations. rcp45_emissions_pathway/The emissions-constraint XML file used to represent the RCP 4.5 pathway. Model-improvement inputs core_retire/Updates coal-fired power plant retirement schedules based on New England ISO. GCAMUSA_IM3_elec_trade_interconnect.xmlRestricts electricity trade to occur within the ERCOT, WECC, and IE interconnections. nuclear_USA.xmlUpdates the retirement schedules of the Diablo Canyon and Palisades nuclear power plants. high_cost_offshore_carbon.xmlUpdates the assumed cost of offshore carbon storage. water_supply_constrained_gleeson_5pct.xmlReplaces WaterGAP historical groundwater-depletion estimates with data from the Gleeson dataset and limits groundwater extraction to 5% of the available groundwater in each Superwell grid cell. How to use the data This dataset is designed for use with the IM3 version of GCAM-USA. Download or clone GCAM-USA from the IM3 GCAM GitHub repository at https://github.com/IMMM-SFA/gcam-core and check out the gcam-usa-im3 branch. Place the downloaded folder im3scenarios in the gcam-core/input directory while preserving the provided folder structure.

Energy↗

Case Study of ISO/TS 6336-22 Micropitting Method: Preprint

ISO/TS 6336-22 (Calculation of load capacity of spur and helical gears — Part 22: Calculation of micropitting load capacity) is the ISO technical specification containing a proposal for a method to calculate the risk of micropitting in gear sets. It assesses micropitting risk through a safety factor which is calculated as the minimum specific film thickness in the contact zone divided by a permissible specific film thickness. A sliding parameter is used to adjust the film thickness in the contact zone to the region of highest sliding, which is where micropitting has been observed. The permissible specific film thickness is best determined through experience or testing, but there is an option to estimate it based on the lubricant’s failure load stage in FZG testing. This paper is a case study of how the method behaves when applied to several gear sets and applications that have experienced micropitting in the field.

gears↗

Case Study of ISO/TS 6336-22 Micropitting Calculation

ISO/TS 6336-22 (Calculation of load capacity of spur and helical gears - Part 22: Calculation of micropitting load capacity) is the ISO technical specification containing a proposal for a method to calculate the risk of micropitting in gear sets. It assesses micropitting risk through a safety factor which is calculated as the minimum specific film thickness in the contact zone divided by a permissible specific film thickness. A sliding parameter is used to adjust the film thickness in the contact zone to the region of highest sliding, which is where micropitting has been observed. The permissible specific film thickness is best determined through experience or testing, but there is an option to estimate it based on the lubricant’s failure load stage in FZG testing. This paper is a case study of how the method behaves when applied to several gear sets and applications that have experienced micropitting in the field.

ENGINEERING,WIND ENERGY↗

Influence of NOx Chemistry on the Prediction of Natural Gas End-Gas Autoignition

Research on the influence of NOx (NO/NO2) chemistry on HC oxidation has shown that NOx plays an important role in the promotion/inhibition of HC autoignition [1-6]. Current data for n-heptane, iso-octane, ethanol, and toluene [3, 4] have shown that NO chemistry inhibits autoignition at low temperatures and concentrations. However, at medium and high temperatures and low concentrations, autoignition is promoted, decreasing the Negative Temperature Coefficient (NTC) effect. This autoignition promotion, however, becomes weaker as NO concentrations are increased. Additionally, fundamental kinetics studies have suggested that NOx chemistry also promotes the autoignition of smaller HC, such as CH4 [7-10], C2H6 [11-14], and C3H8 [15]. Additionally to the chemical kinetics studies, a growing body of evidence supports the importance of NOx chemistry on SI engine simulations [16, 17]. Foong et al. [18] suggested that the addition of NO in their models significantly improved the agreement between simulations and experiments where the onset of knock was advanced due to the presence of NO, and Morganti et al. [19] showed that NO addition in the residual-gas was necessary for their models to obtain good agreement with experimental data. Lastly, Mohr et al. [20, 21] investigated the effect of Natural Gas (NG) reactivity and EGR substitution rate and composition on homogeneous ignition delay, flame speeds, and EGAI for stoichiometric NG/oxidizer/EGR blends. They observed that the addition of EGR composed of only inert species (CO2 and Ar) suppressed homogeneous autoignition in all NG fuels tested under all conditions. However, for all NG fuels tested, increasing EGR rates with reactive species (Ar, CO2, CO, and NO) promoted homogeneous autoignition under all conditions, thus reproducing the same trends for various NG fuel compositions that were observed in other studies and fuels. For this reason, a study is being conducted to analyze the effects of NOx chemistry on the prediction of NG/air/EGR homogeneous autoignition. This study has been divided into two tasks. First, the addition of NOx chemistry to the ARIES82 mechanism [20] is being validated using homogeneous ignition delay data collected by Mohr [20, 21]. Second, once the new modified mechanism with NOx reactions has been validated, it will be employed on engine multi-dimensional modeling presented in [22, 23] to analyze the influence of NOx chemistry on NG EGAI. Results thus far have shown that homogeneous ignition delay calculations are sensitive to NOx chemistry, where the modified mechanisms captured well all trends and closely matched the homogeneous ignition delays observed by Mohr et al. Also, the results in this work suggest that NOx chemistry is necessary to correctly capture the trends in NG homogeneous autoignition when EGR with reactive species is used since the opposite behavior is observed when only inert species are considered for the EGR composition.

03 NATURAL GAS↗

Integrated transient modeling of gas turbine and sCO2 power cycle for exhaust heat recovery application

For distributed generation installations, the transient response of the power generation system is critical to meet power quality (voltage and frequency) requirements. Transient models for gas turbine and supercritical carbon dioxide (sCO2) power cycle were integrated for an exhaust heat recovery bottoming cycle system for a distributed generation application. The transient model for the SGT-750 Siemens gas turbine was a ‘black-box’ functional mockup interface (FMI) model developed by Siemens Industrial Turbomachinery in $Finsp\mathring{a}ng$, Sweden. The SGT-750 is a twin-shaft gas turbine that produces 40 MW electricity with an efficiency of about 40% at ISO conditions. At 100% gas turbine throttle (load), the SGT-750 has average exhaust conditions of 114.6 kg/s and 469.8 °C.

20 FOSSIL-FUELED POWER PLANTS↗

Physically Realistic Estimates of Electric Water Heater Demand Response Resource

Multiple grid integration studies have examined the value of demand response, including from water heaters, to bulk power systems. Common shortcomings of these studies include physically unrealistic assumptions. For example, studies often assume that all electric water heater load can be shed for up to an hour to provide capacity or contingency service, that all electric water heater load is shiftable, and that round-trip efficiencies for shifting service are 100%. Another issue is that simply summing up estimates of individual water heaters' flexibility bounds, an attractive idea for constructing the MW-scale resources necessary for direct inclusion in grid investment and operational models, can result in significant overestimates of actual resource, because, e.g., a water heater with the ability to reduce load may not be able sustain the reduction for as long as the aggregate model suggests is possible. This presentation demonstrates the impact of estimating the flexibility of electric water heaters with physically realistic models suitable for grid service analysis. Electric water heater flexibility representations are constructed based on ResStock simulations of New England. Specifically, we examine contingency resource (related to capacity, shed, and contingency reserve services) and energy shifting resource from electric resistance and heat pump water heaters. Different estimation methods are compared; and the surrogate models' event responses are validated against events directly simulated in EnergyPlus. We also demonstrate the impact of using electric water heaters for contingency reserves and energy shifting in detailed models of possible future ISO New England power systems.

building energy modeling↗

Efficiency and Capacity Performance of a Stirling-Cycle Water-to-Water Heat Pump

The performance of a 10 kW (2.8 ton) heat pump has been modeled in preparation for evaluation in a controlled-atmosphere psychrometric facility. The heat pump uses an electrically driven Stirling engine with nitrogen as a working fluid. The appropriate standards for testing are ANSI/AHRI/ASHRAE ISO Standard 13256-2:1998 (RA 2012), Water-Source Heat Pumps—Testing and Rating for Performance—Part 2: Water-to-Water and Brine-to-Water Heat Pumps. The heating and cooling efficiency and capacity of the device has been modeled at different hot and cold sink temperatures spanning a wide range of possible operating conditions. The heat pump was designed for a seasonal efficiency energy ratio (SEER) of 22. The high efficiency of this product coupled with the use of nitrogen as a working fluid makes it an important tool for the decarbonization of residential, commercial, and industrial HVAC&R applications.

Kowalski, Steve↗

Noodles: Cooking Up Collaborative Visualization

NOODLES is a new cross-domain collaborative visualization and analysis capability being developed at NREL. The NOODLES specification is a minimal protocol that can tie different software packages and platforms together. As an example, a simulation code that speaks this protocol could stream iso-surfaces to an immersive VR space and a web browser. Another example is a team (with some members across the country) classifying and discovering features in a statistical data plot, driven from a researcher's existing Python-based workflow. In this talk, we will discuss some background on the problems that this protocol intends to solve, basic principles of the specification, the current state of supporting libraries, and some demonstrations of the protocol in action.

3D↗

Use of Machine Learning on PMU Data for Transmission System Fault Analysis

Synchrophasor technology has been used for monitoring, control, and protection of bulk power system for over 10 years. Deployment of phasor measurement units (PMUs) in the USA power system has surpassed 3000 units installed in the transmission substations as stand-alone intelligent electronic devices (IEDs) or as a software add-on to other devices such as digital protective relays (DPRs) or digital fault recorders (DFRs). By now, thousands of terabytes of PMU data may have been captured and stored by various transmission system operators (TSOs) and independent system operators (ISOs). This creates an opportunity to deploy advanced machine learning (ML) techniques to detect and classify faults recorded by PMUs automatically to be used by the system operators for rapid, critical decision-making when manual analysis of the past or unfolding events is not feasible. In this paper we offer a brief background on how the automated fault analysis may be done using DPR and/or DFR data, and compare some of the legacy approaches to the new ML approaches in the context of the system-wide PMU recordings. We then offer insights from developing practical ML solutions that have been applied on field recordings captured by close to 450 PMUs from all three US interconnections (Western, Eastern and ERCOT) over two years (2016-2017). We identify and illustrate ML challenges we addressed: inaccurate data, data with scarce and temporally imprecise fault labels, data recorded by PMUs sparsely located at substations resulting in the fault records taken afar from the ends of the faulted lines, data containing only positive sequence values, and data taken at different voltage levels. We then illustrate the ML model results for fault analysis under different application scenarios. The novelty of this study is not only in the design, implementation, and performance analysis of the ML algorithms, but also in the use of advanced fault modelling and simulation approaches to improve the training results when developing supervised ML models for fault detection and classification. Extensive simulations of faults were conducted on a 14-bus power system to create a training dataset with over 1400 accurately labelled faults. This dataset was applied to enhance the accuracy of fault detection and classification of machine learning-based models trained with small number of labelled faults in large datasets recorded in the grid interconnections ranging from 5,000 to 70,000 buses.

Synchrophasors, Machine Learning, Fault Analysis, ↗

Results of ISO/TS 6336-22 Evaluating Full Contact Zone

ISO/TS 6336-22 (Calculation of load capacity of spur and helical gears - Part 22: Calculation of micropitting load capacity) is the ISO technical specification containing a proposal for calculations of the risk of micropitting in gear sets. Micropitting is a Hertzian fatigue phenomenon that appears as ultra-fine cracking and pitting on the flanks of gear teeth. Since progressive micropitting can lead to macropitting and flank damage, critical applications such as wind turbines, marine drives, and high-speed gear drives seek to accurately predict whether their designs are susceptible to this damage. ISO/TS 6336-22 assesses micropitting risk through a safety factor which is calculated as the minimum specific film thickness in the contact zone divided by a permissible specific film thickness. In the previous paper, the calculations were performed using the simplified method (Method B) that evaluates points on the path of contact. This was done for three gear sets that experienced micropitting in operation. The minimum specific film thickness for the two field cases was very high, which indicates that the gears were operating in the full elastohydrodynamic lubrication (EHL) regime. A more accurate calculation for these cases (Method A) calculates the specific film thickness across the entire contact zone. This paper applies this Method to the case study from the previous paper. The results are compared to micropitting observed in operation. Results are also compared to the results of the previous paper. Conclusions are made regarding the accuracy of both Methods compared to the field cases and relative to each other.

ENGINEERING,WIND ENERGY↗

Results of ISO/TS 6336-22 Evaluating Full Contact Zone: Preprint

ISO/TS 6336-22 (Calculation of load capacity of spur and helical gears — Part 22: Calculation of micropitting load capacity) is the ISO technical specification containing a proposal for calculations of the risk of micropitting in gear sets. Micropitting is a Hertzian fatigue phenomenon that appears as ultra-fine cracking and pitting on the flanks of gear teeth. Since progressive micropitting can lead to macropitting and flank damage, critical applications such as wind turbines, marine drives, and high-speed gear drives seek to accurately predict whether their designs are susceptible to this damage. ISO/TS 6336-22 assesses micropitting risk through a safety factor which is calculated as the minimum specific film thickness in the contact zone divided by a permissible specific film thickness. In the previous paper, the calculations were performed using the simplified method (Method B) that evaluates points on the path of contact. This was done for three gear sets that experienced micropitting in operation. The minimum specific film thickness for the two field cases was very high, which indicates that the gears were operating in the full elastohydrodynamic lubrication (EHL) regime. A more accurate calculation for these cases (Method A) calculates the specific film thickness across the entire contact zone. This paper applies this Method to the case study from the previous paper. The results are compared to micropitting observed in operation. Results are also compared to the results of the previous paper. Conclusions are made regarding the accuracy of both Methods compared to the field cases and relative to each other.

gearbox↗

Results of ISO/TS 6336-22 Evaluating Full Contact Zone

ISO/TS 6336-22 (Calculation of load capacity of spur and helical gears - Part 22: Calculation of micropitting load capacity) is the ISO technical specification containing a proposal for calculations of the risk of micropitting in gear sets. Micropitting is a Hertzian fatigue phenomenon that appears as ultra-fine cracking and pitting on the flanks of gear teeth. Since progressive micropitting can lead to macropitting and flank damage, critical applications such as wind turbines, marine drives, and high-speed gear drives seek to accurately predict whether their designs are susceptible to this damage. ISO/TS 6336-22 assesses micropitting risk through a safety factor which is calculated as the minimum specific film thickness in the contact zone divided by a permissible specific film thickness. In the previous paper, the calculations were performed using the simplified method (Method B) that evaluates points on the path of contact. This was done for three gear sets that experienced micropitting in operation. The minimum specific film thickness for the two field cases was very high, which indicates that the gears were operating in the full elastohydrodynamic lubrication (EHL) regime. A more accurate calculation for these cases (Method A) calculates the specific film thickness across the entire contact zone. This paper applies this Method to the case study from the previous paper. The results are compared to micropitting observed in operation. Results are also compared to the results of the previous paper. Conclusions are made regarding the accuracy of both Methods compared to the field cases and relative to each other.

gearbox↗