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At least 973 records · Page 54

Simulations of droplet combustion under gas turbine conditions

In various applications with recirculation, liquid droplets can be immersed in gases that may have a wide range of possible compositions, from pure air to hot combustion products. In order to gain fundamental understanding of the behaviour of individual droplets in vitiated air, numerical simulations of kerosene single droplet evaporation, autoignition, and combustion in conditions relevant to gas turbines have been performed. The droplet autoignition behaviour has been analysed in both physical and mixture fraction space for a wide range of vitiated air compositions and initial droplet diameters. Results show that the autoignition time delay decreases with increasing level of dilution with hot combustion products and decreasing initial droplet diameter. Chemistry is confined up to a radius of almost 10 initial droplet diameters and the location of autoignition is influenced by both the initial droplet diameter and the level of dilution. The time evolution of species in the gaseous phase after autoignition shows similar trends for all the diameters and dilution levels investigated here with the peak of temperature and OH mass fraction moving towards the droplet surface as a consequence of the balance between fuel production and consumption. In mixture fraction space, the location of the peaks of temperature and OH mass fraction after autoignition do not change in time whereas other intermediate species such as CH 2 O and pyrolysis products still exhibit a quite variable behaviour. The long-time flame structure has been compared with gaseous laminar counterflow simulations and, although qualitatively similar, the flame structure in the two configurations has differences with implications for flamelet combustion models used in spray combustion. The droplet evaporation, autoignition, and combustion behaviour has been summarized through a regime diagram showing the evaporation and autoignition time delays as a function of both initial droplet diameter and vitiated air dilution. This allows the identification of different states in the droplet combustion scenario and the introduction of critical values of dilution and initial droplet diameter beyond which single droplet rather than cloud combustion can occur, which can be exploited in the design of lean burn gas turbine combustion systems. In conclusion, the approach presented here can be easily extended to other conditions and fuels allowing the generation of regime diagrams for various operating conditions.

42 ENGINEERING↗

Auto-ignitive deflagration speed of methane (CH 4 ) blended dimethyl-ether (DME)/air mixtures at stratified conditions

Front propagation speeds from fully resolved unsteady one dimensional simulations with dimethyl-ether (DME)/methane (CH 4 )/air mixtures under engine relevant conditions are presented using complex kinetics and transport. Different time-scales of monochromatic inhomogeneities in DME concentration with varying DME/CH 4 blending ratios are simulated to unravel the fundamental aspects of auto-ignition and flame propagation under the influence of reactivity stratification. To understand the influence of different stratification time-scales on the flame-ignition interaction, two sets of conditions are simulated such that low temperature chemistry is present in only one of them. For a given amplitude of stratification, it is found that the instantaneous propagation speed is significantly affected by the level of CH 4 concentration in the binary fuel blend. Specifically, for cases with low temperature chemistry, at relatively smaller time-scales, the overall fluctuation in the instantaneous propagation speed is found to subside as the level of CH 4 concentration in the mixture is increased. However, for both sets of conditions, at comparatively larger time-scales, a rapid change in the instantaneous propagation speed is observed with an increase in the level of CH 4 concentration in the mixture. The intrinsic effects of stratification time-scales on the low temperature chemistry and the high temperature chemistry are further examined to assess the flame-ignition interaction. A displacement speed analysis is also carried out to elucidate the underlying combustion modes that are responsible for such a variation in flame response.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Application of a temporal multiscale method for efficient simulation of degradation in PEM Water Electrolysis under dynamic operating conditions

Hydrogen is emerging as a vital energy carrier, driven by the need to reduce carbon emissions. Proton Electrolyte Membrane Water Electrolysis (PEMWE) enables hydrogen production under fluctuating renewable power conditions but requires improved understanding and stability of the anode catalyst layer under dynamic operating conditions, especially with low noble metal loadings. Long-term degradation experiments are both time-consuming and costly; therefore, a systematic, model-aided approach is essential. In the present work, a temporal multiscale method is applied to reduce the computational effort of simulating long-term degradation processes in PEMWE, with an exemplary focus on catalyst dissolution. A mechanistic model incorporating the oxygen evolution reaction, catalyst dissolution, and hydrogen permeation from the cathode to the anode was hypothesized and implemented. In this way, the local periodicity of transport and reaction processes in dynamic PEMWE operation, which influence the gradual degradation of the catalyst layer, is captured. The temporal multiscale method significantly reduces the computational effort of simulation, decreasing processing time from hours to mere minutes. This efficiency gain is attributed to the limited evolution of Slow-Scale variables during each period of time P of the Fast-Scale variables. Consequently, simulation is required only until local periodicity is achieved within each Slow-Scale time step. Hence, the fully resolved dynamic problem is decoupled into these two scales, employing a heterogeneous multiscale technique. The developed approach effectively accelerates parameter estimation and predictive simulations, supporting systematic modeling of PEMWE degradation under dynamic conditions.

08 HYDROGEN↗

Effect of nickel on the oxidation behavior of FeCrAl alloy in simulated PWR and BWR conditions

FeCrAl alloys are being investigated as candidate materials for light water reactor fuel claddings. The chemical composition of FeCrAl determines its resistance to corrosion under normal operating conditions. The purpose of this paper is to investigate the effect of 0, 1, 3 wt% Ni addition on the passivation characteristics of Fe17Cr5.5Al in oxygenated and hydrogenated simulated reactor waters for 3-month immersion. Current results show that Ni addition improves the passivation of FeCrAl under oxygenated condition and decreases the mass loss under hydrogenated conditions.

36 MATERIALS SCIENCE↗

Pavement condition and climatic data in southeast Texas: A dataset for evaluating flood impacts on pavement performance

Effective pavement maintenance is essential for economic stability, optimal network performance, and roadway safety. Achieving this requires thorough evaluation of pavement conditions, including structural integrity, surface roughness, and distress characteristics. Pavement performance indicators play a critical role in influencing vehicle safety and ride quality. Recent advances have emphasized the use of data-driven modeling to anticipate pavement behavior, with the goal of optimizing resource allocation and refining Maintenance and Rehabilitation (M&R) strategies through accurate condition assessment. A foundational requirement for these modeling efforts is the availability of standardized, high-quality datasets that can support robust and reproducible infrastructure analysis. This data article presents a comprehensive dataset assembled to facilitate pavement performance prediction, with a geographic focus on Southeast Texas, particularly the flood-vulnerable area of Beaumont. The dataset encompasses pavement and traffic attributes, meteorological records, flood simulation outputs, ground deformation measurements, and topographic indices, enabling detailed examination of both load-associated and non-load-associated degradation mechanisms. Data preprocessing was performed using ArcGIS Pro, Microsoft Excel, and Python to ensure consistency and usability in data-driven modeling applications, including machine learning workflows. Key contributions of this dataset include its utility in analyzing the climatic and environmental factors affecting pavement conditions, identifying critical predictive features, and enabling in-depth correlation analysis across diverse variables. By filling existing gaps in input variable selection resources, this dataset supports the development of predictive tools for estimating future maintenance demand and enhancing the resilience of pavement networks in flood-impacted areas. The resource highlights the importance of standardized datasets for advancing pavement management practices and provides a robust foundation for ongoing infrastructure performance modeling.

42 ENGINEERING↗

High-Resolution South American Wind Resource Data Downscaled with Generative Machine Learning Conditioned on Near-Surface Observations

High-resolution historical wind data was developed for the entirety of South America using the innovative Super-Resolution for Renewable Resource Data (sup3r) machine learning framework. The publicly available Sup3rWind South America dataset represents a significant advancement in wind resource data generation, leveraging generative machine learning conditioned on near-surface observations from the Meteorological Assimilation Data Ingest System (MADIS) to efficiently and accurately downscale coarse reanalysis data from the European Centre for Medium-Range Weather Forecasts (ERA5). This approach produces fine-scale, spatially and temporally coherent wind and meteorological fields hundreds of times more computationally efficient than traditional numerical weather modeling methods, enabling access to high-fidelity wind information across both continental and offshore regions. Sup3rWind South America builds on the earlier Sup3rWind Ukraine dataset through improvements in model architecture and outputs conditioned on near-surface observation inputs. As with the Ukraine data release, this dataset includes wind speed, wind direction, temperature, relative humidity, and pressure at a horizontal resolution of ~2 km, representing a 15x spatial enhancement relative to the 31 km ERA5 grid. Wind speed and direction are provided at 5-minute resolution, a 12x temporal refinement compared to the hourly ERA5 data, while temperature, relative humidity, and pressure remain at hourly resolution. The data covers all years from 2005 to 2024. Before downscaling, ERA5 inputs were bias-corrected using long-term monthly means and a limited number of quality-controlled observations to align large-scale statistics with regional conditions. The resulting dataset is the first publicly available high-resolution timeseries wind record that provides full spatial coverage of South America. Model validation demonstrates strong agreement with observations across several statistical metrics, consistent with other state-of-the-art high-resolution wind resource datasets. The potential applications of Sup3rWind South America span renewable energy resource assessment, energy system modeling, and grid resilience analysis. The 20-year record and high spatial and temporal resolution support accurate estimation of long-term energy yield and the economic feasibility of potential wind development sites. Continuous coverage across both continental and offshore regions enables comprehensive site prospecting within exclusive economic zones. The 2 km, 5-minute resolution data provide the spatial and temporal variability required for power system simulation, operational planning, and regional risk assessments.

17 WIND ENERGY↗

Thermal performance of a Concrete Cool Roof under different climatic conditions of Mexico

A cool roof is an ordinary roof with a reflective coating on the exterior surface which has a high solar reflectance and high thermal emittance. These properties let the roof keep a lower temperature than a standard roof under the same conditions. In this work, the thermal performance of a concrete roof with and without insulation and with two colors has been analyzed using the finite volume method. The boundary conditions of the external roof surface were taken from hourly averaged climatic data of four cities. For the internal surface, it is considered that the building is air-conditioned and the inside air has a constant temperature. The interior surface temperature and the heat flux rates into the roofs were obtained for two consecutive days in order to assess the benefits of a cool roofs in different climates.

36 MATERIALS SCIENCE↗

Disjunctive linear separation conditions and mixed-integer formulations for aircraft conflict resolution

In this paper, we address the aircraft conflict resolution problem in air traffic control. We introduce new mixed-integer programming formulations for aircraft conflict resolution with speed, heading and altitude control which are based on disjunctive linear separation conditions. We first examine the two-dimensional aircraft conflict resolution problem with speed and heading control represented as continuous decision variables. We show that the proposed disjunctive linear separation conditions are equivalent to the classical nonlinear conditions for aircraft separation. Further, we characterise conflict-free trajectories based on aircraft velocity bounds and propose a simple pre-processing algorithm to identify aircraft pairs which are either always conflict-free, or which cannot be separated using speed and heading control only. We then incorporate altitude control and propose a lexicographic optimisation formulation that aims to minimise the number of flight level changes before resolving outstanding conflicts via two-dimensional velocity control. The proposed mixed-integer programming formulations are nonconvex, and we propose convex relaxations, decomposition methods and constraint generation algorithms to solve the two-dimensional and lexicographic optimisation formulations to guaranteed optimality. Numerical experiments on four types of conflict resolution benchmarking instances are conducted to test the performance of the proposed mixed-integer formulations. Further, the proposed method is compared against two benchmarks based on state-of-the-art approaches for the aircraft conflict resolution problem. Our numerical results show that the proposed method largely outperforms both benchmarks in terms of runtime and is able to solve significantly more instances to global optimality.

97 MATHEMATICS AND COMPUTING↗

Thermoelectric air conditioning undergarment for personal thermal management and HVAC energy saving

Personal thermal management systems (PTMS) are highly desirable for improving individual thermal comfort and reducing indoor HVAC energy consumption. Although there have been many attempts in developing PTMS, existing PTMS are generally bulky, heavy or immobile. Besides, previous analysis on additional personal cooling and heating power required for maintaining thermal comfort in changing environments did not consider the individual difference in metabolism and the variability of comfort skin temperature with environmental conditions. In this paper, we report on the development of a novel lightweight (<1 kg) thermoelectric air conditioning undergarment system with a preferred design of branching tubing network (branching angle of 60° and diameter ratio of 0.782) for air distribution. Through thermal manikin and human subject tests, we demonstrated that the novel system is capable of providing a maximum of 15.5 W of personal cooling and 18.1 W personal heating with a coefficient of performance (COP) greater than 0.4, which is sufficient to the expansion of the indoor set-points by at least 2.2 °C (4 °F) on both sides without compromising thermal comfort and the potential saving of about 15% HVAC energy. Furthermore, our study improved the understanding of the required additional personal cooling and heating power for changing environmental conditions, which are essential guidelines for the further development of PTMS.

42 ENGINEERING↗

Refining seasonal performance metrics for room air-conditioning in emerging markets: Integrating building simulations with real-world equipment performance data

Buildings significantly impact worldwide energy consumption, emphasizing the need to reduce the cooling energy demand, especially in warm climates. Minimum energy performance standards (MEPS) and seasonal performance metrics such as the Cooling Seasonal Performance Factor (CSPF) are crucial for improving room air conditioning (RAC) efficiency. However, challenges remain, particularly in emerging markets like Brazil, where seasonal performance metrics have recently been introduced. This study assesses the factors influencing country-level seasonal efficiency metrics and proposes a framework to refine these calculations by considering local climates and expected RAC usage in real-world households via building simulations. Key considerations include outdoor air temperature binning for different climates, RAC usage patterns (i.e., daytime and nighttime usages), envelope thermal performance of households, and urban heat island (UHI) effects. The results reveal that CSPF values can vary significantly based on climate conditions, with observed CSPF ranging from 4.10 to 11.59 Wh/Wh across 577 Brazilian climates. The inclusion of UHI effects led to a reduction in CSPF values by up to 29% during nighttime operations in hot urban areas. Additionally, building envelope efficiency showed contrasting impacts on RAC performance, with CSPFs reaching up to 15.35 Wh/Wh under specific optimized conditions. These findings highlight the need for transparent policymaking in RAC performance databases, facilitating the application of approaches like those proposed in this study and supporting diverse stakeholders in decision-making.

Bavaresco, Mateus↗

A path-dependent fatigue crack propagation model under non-proportional modes I and III loading conditions

It has been well established that fatigue damage process is load-path dependent under non-proportional multi-axial loading conditions. Most of studies to date have been focusing on interpretation of S-N based test data by constructing a path-dependent fatigue damage model. Our paper presents a two-parameter mixed-mode fatigue crack growth model which takes into account of crack growth dependency on both load path traversed and a maximum effective stress intensity attained in a stress intensity factor plane (e.g.,KI-KIII plane). Furthermore, by taking advantage of a path-dependent maximum range (PDMR) cycle definition (Dong et al., 2010; Wei and Dong, 2010), the two parameters are formulated by introducing a moment of load path (MLP) based equivalent stress intensity factor range (ΔKNP) and a maximum effective stress intensity parameter KMax incorporating an interaction term KI·KIII. To examine the effectiveness of the proposed model, two sets of crack growth rate test data are considered. The first set is obtained as a part of this study using 304 stainless steel disk specimens subjected to three combined non-proportional modes I and III loading conditions (i.e., with a phase angle of 0°, 90°, and 180°). The second set was obtained by Feng et al. (2007) using 1070 steel disk specimens subjected to similar types of non-proportional mixed-mode conditions. Once the proposed two-parameter non-proportional mixed-mode crack growth model is used, it is shown that a good correlation can be achieved for both sets of the crack growth rate test data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Adaptation of virtual synchronous generators to dynamic conditions in power grids

Virtual synchronous generators (VSGs) are widely adopted as grid-forming controls for inverter-based resources. However, when grid conditions vary significantly as characterized by changes in short-circuit ratio (SCR) and the reactance-to-resistance (X/R) ratio, fixed-gain designs and the commonly used P–Q decoupling assumption can become inaccurate. Such conditions can degrade transient power performance, leading to oscillations, prolonged settling, and overshoot, particularly in stiff-grid operating points. This paper quantifies how grid strength and impedance-dependent coupling affect the active–reactive power dynamics of a conventional VSG over a broad range of SCR and X/R values. An adaptive VSG tuning framework is then developed by combining (i) a coupling-explicit, impedance-parameterized state-space model to enable systematic controller synthesis, (ii) a full-state-feedback law designed via pole placement to meet prescribed damping and settling-time specifications, and (iii) a physics-informed neural network (PINN)–based online grid-impedance estimator that updates controller gains in real time as grid conditions vary. Offline simulations in MATLAB/Simulink and real-time validation on an OPAL-RT platform show that the proposed method preserves consistent damping and settling behavior with reduced overshoot across wide SCR and X/R ranges, compared with fixed-gain VSG baselines.

Adaptive control↗

Direct conversion of wet algae to crude biodiesel under supercritical ethanol conditions

This paper presents a single-step, environmentally friendly approach for the direct conversion of wet algae to crude biodiesel under supercritical ethanol conditions. Ethanol was used for the simultaneous extraction and transesterification of lipids in algae to produce fatty acid ethyl esters at supercritical conditions. In this work the effects of process parameters dry algae to ethanol (wt./vol.) ratio (1:6-1:15), reaction temperature (245-270 C), and reaction time (2-30 min.) on the yield of fatty acid ethyl esters (FAEE) were studied. 67% conversion was achieved at 265 C and 20 min of reaction time. The calorific value of a purified biodiesel sample produced at optimum conditions was measured to be 43 MJ/kg, which is higher than that of fatty acid methyl esters produced from the same biomass. The purified fatty acid ethyl esters were analyzed using GC-MS and FTIR. TGA analysis of algal biomass and purified FAEE was presented along with TEM images of the biomass captured before and after supercritical ethanol transesterification. This green conversion process has the potential to provide an energy-efficient and economical route for the production of renewable biodiesel production.

09 BIOMASS FUELS↗

Hydrotreating pine-derived catalytic fast pyrolysis oil to jet fuel: Process durability and impact of operating conditions

Hydrotreating woody biomass-derived catalytic fast pyrolysis (CFP) oil to jet fuel has the potential to enhance energy security due to the large abundance of forest and woody resources. CFP oil produced from pine over ZSM-5 was hydrotreated over sulfided NiMo/Al 2 O 3 for 410 h to study the impact of hydrotreating conditions (pressure, temperature, and weight hourly space velocity (WHSV)). The degree of deoxygenation remained high across the tested hydrotreating conditions, and the products contained < 0.01 wt% oxygen. Increasing hydrotreating pressure from 84 to 125 bar enhanced hydrogenation of aromatic rings and the formation of cycloalkanes and increasing the temperature from 385 to 400 degrees C enhanced cracking and the formation of jet-range molecules. Decreasing the weight hourly space velocity from 0.2 to 0.1 g/(g cat h) further enhanced cracking and led to higher gasoline- and lower jet fuel-range fractions. The highest jet fuel fraction (49 wt%) was obtained at 400 degrees C, 125 bar, 0.2 g/(g cat h) WHSV. CFP oils produced from pine over phosphorous-modified ZSM-5 were hydrotreated at this condition for 588 h to investigate the process durability. The hydrogenation performance of the catalyst gradually stabilized in approximately 300 h after which the product composition remained constant. Of the final hydrotreated CFP oil, 53 wt% fell in the jet fuel range with most of the tested fuel properties meeting ASTM D4054 and/or ASTM D7566 specifications. The freeze points were < -50 degrees C vs. guideline of < -40 degrees C and the viscosities at -20 degrees C were 3.8-4.1 mm 2 /s vs guideline of 8 mm 2 /s. Increasing the fraction of cycloalkanes could increase the cetane number and heating value, which did not meet the guidelines.

09 BIOMASS FUELS↗

Subsoil organo-mineral associations under contrasting climate conditions

Climate differences can induce profound changes in organo-mineral associations in soils. However, the magnitude of these modifications, whether as a direct effect of climate conditions or an indirect effect through changes in soil mineralogy, are still not fully understood. In this study, we aimed to improve understanding of how climate and resultant changes in soil mineralogy affect subsoil (i.e., 0.4–0.9 m) organo-mineral interactions at the macro- and microscale. A set of subsoil samples were collected throughout an elevation gradient (approximately 1800 to 2400 mm precipitation year –1 and 15 to 24ºC) on Kohala Mountain, Hawaii. We carried out a combined approach of bulk soil analyses with mineral extractions and spectroscopic and spectromicroscopic analyses. Significant positive correlations (p < 0.05) between soil organic carbon (SOC) with extracted Fe and Al (dithionite citrate bicarbonate – DCB and ammonium oxalate – OX) at the bulk soil scale supported prior research showing concurrent decline of subsoil Fe, Al and SOC above a precipitation level of ~2000 - ~2200 mm year -1 . However, divergence in microscale organo-mineral associations identified using NanoSIMS allowed us to discern the relative roles of Fe and Al in promoting organo-mineral associations. At the lower precipitation range (~1800 mm year -1 ), the clay fraction < 2 µm showed higher amounts of organic matter (OM) co-localized with Fe & Al compared with the higher precipitation level (~2300 mm year -1 ), where OM was mostly unassociated or only associated with Al. While Fe contributed to approximately 40% of the microscale organo-mineral associations in the lower precipitation site (quantified by co-localizations with OM segments), this contribution at the higher rainfall regime was only 5%. In contrast, the contribution of Al was approximately the same in both rainfall levels (approximately 30%). Therefore, associations with Al may be more important than Fe for OM stabilization under reducing climate conditions. The normalized CN:C ratio based on individual pixels was found to be higher when co-localized with Al, Fe, or both, especially under the high precipitation regime. This fact points towards the importance of Fe and Al to stabilize more N-rich OM, especially at high rainfall levels. In addition, subsoil from higher rainfall conditions exhibited more reduced forms of Fe (assessed by Fe K-edge XANES) and lower proportions of carboxyl-C (5% lower in the relative abundance) as well as higher alkyl/O-alkyl ratios determined by CP-MAS 13C NMR. Such differences in composition may directly influence the organo-mineral associations at both locations, as differences in Fe reduction and the presence of carboxyl-C groups are recognized to play a role in OM stabilization. We conclude that spatial relationships between Fe and Al with SOC at the microscale show a shift towards Al-dominated SOC associations at higher precipitation that could not be ascertained from bulk measurements alone. Therefore, they are of fundamental importance to understand the impact of climate change on SOC stabilization.

54 ENVIRONMENTAL SCIENCES↗

The solubility of thorium in carbonate-bearing solutions at hydrothermal conditions

Thorium mineralization is frequently hosted in carbonate-bearing rocks, and thorium commonly substitutes into the structures of carbonate-bearing minerals that have precipitated from or been modified by hydrothermal fluids. Given this common association, it is reasonable to consider the hypothesis that the presence of carbonate ligands in hydrothermal solutions promotes the transport of Th through the formation of stable aqueous complexes. Our ability to evaluate this hypothesis, however, is hindered by the lack of experimental data for Th-carbonate species at conditions beyond ambient. The low-temperature data indicate that carbonate is a strong complexing agent for Th. In this contribution, we investigate the solubility of Th in carbonate-bearing fluids relevant to natural systems (0.05–0.5 m NaHCO 3 /Na 2 CO 3 ; pH T ~ 7.8–9.8) at elevated temperature (175–250 °C). We demonstrate that, in contrast to the behavior of Th at low temperature, the stability of Th-carbonate complexes is not sufficient for them to predominate at these conditions. Instead, the solubility of Th is governed by hydrolysis reactions. Under the experimental conditions investigated, the predominant hydroxyl complexes are Th(OH) 4 0 and Th(OH) 5 -. Furthermore, thermodynamic formation constants were derived for these species at the temperatures considered in our experiments (log β 4 = 43.34 and 44.31 at 175 and 200 °C, respectively, and log β 5 = 46.15 and 47.9 at 225 and 250 °C, respectively) to permit forward modeling of Th mobility in natural systems. Our study indicates that carbonate ions are unlikely to play a role in transporting Th in hydrothermal fluids. Summarizing the results of this study and our previous studies of the solubility of Th in hydrothermal fluids, we conclude that SO 4 2- is the primary ligand responsible for the hydrothermal transport of Th.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine learning assisted bayesian inference of mix and hot-spot conditions in NIF implosions

Experiments on the National Ignition Facility (NIF) have provided clear evidence of ablator material mixing into the Hot-Spot, leading to degraded performance. However, inferring the amount of mix and Hot-Spot conditions from typical experimental observations (e.g. x-ray spectra and images) is highly challenging. Here, we have developed an analysis method that utilizes machine learning assisted Bayesian inference to find the probability distributions of the Hot-Spot and mix conditions. This approach uses a neural network, trained on an idealized 2-dimensional representation of the Hot-Spot and mix distribution, and Bayesian inference to find the statistical distributions of Hot-Spot conditions that provide a match with observations. We have tested this method with synthetic data from simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Feasibility study for test rig assessments of fish passage conditions in a Kaplan turbine

The assessment of fish passage conditions in hydroelectric turbines consists of identifying and quantifying physical magnitudes leading to increased risks of injury of fish passing through turbines in operation. Such assessments are usually carried out either with the use of computer-based methods during design or with field testing of live fish and sensors passing through prototypes. A method in between consists of test rig experimentation, which is critical for testing fish-focused design concepts and offers the opportunity for implementing the most effective design measures for improved fish survivability. However, fish-related assessments in test rigs are not sufficiently documented for industrial applications. This work presents the main findings of an experimental campaign to quantify fish-related hydraulic magnitudes in a physical model of a Kaplan turbine in a commercial test rig. Two operating conditions were tested by releasing miniaturized autonomous sensor devices (termed Sensor Fish Mini) at the turbine intake flow, passing them through the runner in motion and recovering them at the draft tube exit. During passage, time series of acceleration, absolute pressure and rotational velocity were recorded. The recordings were then interpreted to determine the magnitude and likely location of hydraulic stressors hazardous to fish. The statistical tests on the reported measurements indicated that low pressure, collisions on the runner and rotations in the draft tube were not different between the two tested operating points. On the other hand, pressure drop and collision rates on the distributor differed considerably as a function of net head. The outcomes of this investigation showed that test rig evaluations of fish-related properties with Sensor Fish Mini can contribute to an evidence-based development of turbine geometries designed for providing safer passage conditions. Future work will investigate the scaling of test rig measurements to hydraulically equivalent magnitudes in the prototype and their biological consequences.

13 HYDRO ENERGY↗