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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 109 records · Page 6
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DOE OSTI2022

Computational Methods to Characterize Panel Loading Conditions for Accelerated Testing

Panel cracking and degradation due to wind loading are known to have a detrimental effect on power output. Recreating these damaging conditions in a controlled experimental setting requires an understanding of the loads being generated at the panel surface as a function of both wind speed, wind direction, and panel orientation. To better understand these relationships, a computational fluid dynamics (CFD) simulation package was constructed using an open-source Python library for solving partial differential equations with the finite element method. This CFD package allows the simulated wind speed and panel orientation of a multi-panel array to be easily changed and provides the capability to measure the traction forces at discrete points along the sun-facing and ground-facing surface of an interior panel residing in the wake of one or more upstream panels. A parameter exploration was performed in which the panel angle was varied in even increments from -70 deg to 70 deg and the wind speed was varied from 2 to 30 m/s. During post processing, the measured traction along the panel surface was averaged spatially and interpreted as a time-varying signal, where further processing of this signal yielded the root mean square amplitude and a characteristic frequency associated with the loading. This study found that higher wind speeds are generally associated with increased amplitude of loading and that the panel orientation angle can significantly exacerbate or mitigate this loading. These outcomes are presented along with current work on higher-fidelity verification simulations and recommendations for performing accelerated experimental testing.

loading↗
DOE OSTI2016

Relativistic electron beam driven longitudinal wake-wave breaking in a cold plasma

Space-time evolution of a relativistic electron beam driven wake-field in a cold, homogeneous plasma is studied using 1D-fluid simulation techniques. It is observed that the wake wave gradually evolves and eventually breaks, exhibiting sharp spikes in the density profile and sawtooth like features in the electric field profile [Bera et al., Phys. Plasmas 22, 073109 (2015)]. It is shown here that the excited wakefield is a longitudinal Akhiezer-Polovin mode [A. I. Akhiezer and R. V. Polovin, Sov. Phys. JETP 3, 696 (1956)] and its steepening (breaking) can be understood in terms of phase mixing of this mode, which arises because of relativistic mass variation effects. Further, the phase mixing time (breaking time) is studied as a function of beam density and beam velocity and is found to follow the well known scaling presented by Mukherjee and Sengupta [Phys. Plasmas 21, 112104 (2014)].

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

RANS Simulation VBM of Array of Three Coaxial Lab Scaled DOE RM1 MHK Turbine with 5D Spacing

Attached are the .cas and .dat files along with the required User Defined Functions (UDFs) and look-up table of lift and drag coefficients for the Reynolds Averaged Navier-Stokes (RANS) simulation of three coaxially located lab-scaled DOE RM1 turbine implemented in ANSYS FLUENT CFD-package. The lab-scaled DOE RM1 is a re-design geometry, based of the full scale DOE RM1 design, producing same power output as the full scale model, while operating at matched Tip Speed Ratio values at reachable laboratory Reynolds number (see attached paper). In this case study the flow field around and in the wake of the lab-scaled DOE RM1 turbines in a coaxial array is simulated using Blade Element Model (a.k.a Virtual Blade Model [VBM]) by solving RANS equations coupled with k-\omega turbulence closure model. It should be highlighted that in this simulation the actual geometry of the rotor blade is not modeled. The effect of turbine rotating blades are modeled using the Blade Element Theory. This simulation provides an accurate estimate for the performance of each device and structure of their turbulent far wake. The results of these simulations were validated against the developed in-house experimental data. Simulations for other turbine configurations are available upon request.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Two-Phase Turbulent Kinetic Energy Budget Computation in Co-Current Taylor Bubble Flow

Simulation of two-phase flows is relevant for reactor design and safety at normal operation or during accident scenarios. Often, the two-phase flow is in a regime in which slugs are formed or where the flow stratifies. Modeling such situations using standard single-phase Reynolds-averaged Navier-Stokes (RANS) turbulence models fails due to an overestimation of the eddy viscosity at the resolved two-phase interface. To solve this, an ad hoc turbulence damping term has been proposed in the literature that reduces the turbulence production locally at a two-phase interface, analogously to turbulence wall functions. However, this approach must be tailored to the specific setting and does not consider physical contributions such as surface tension or flow topology. Therefore, the problem of two-phase interfacial turbulence must be studied more in-depth. In this work, we consider co-current turbulent Taylor bubble flow using high-fidelity numerical simulation. The Basilisk code is used to simulate a Taylor bubble rising in a vertical pipe. By simulating the bubble in a moving frame of reference, we may study the turbulent kinetic energy (TKE) budgets ahead of the bubble, in its wake, and across the interface. The implementation of the TKE budget computation and the underlying averaging techniques are validated for the single-phase region ahead of the Taylor bubble using reference direct numerical simulation data. The analysis of the TKE budgets in the setting of Taylor bubble flow allows for the study of how turbulence behaves due to the presence of a two-phase interface and, in turn, supports the improvement of two-phase RANS models.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Generation of attosecond electron bunches upon laser pulse propagation through a sharp plasma boundary

The formation of an electron bunch produced due to electron self-injection into a wake wave that is generated by a relativistic-intensity laser pulse propagating through a sharp boundary of semi-bounded plasma is studied in one-dimensional geometry. Analytical expressions are obtained for estimating the bunch length and the energy spread of electrons in the bunch. Numerical simulation is performed which confirms the results of analytical consideration. (paper)

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Probabilistic neural networks for fluid flow surrogate modeling and data recovery

We consider the use of probabilistic neural networks for fluid flow surrogate modeling and data recovery. This framework is constructed by assuming that the target variables are sampled from a Gaussian distribution conditioned on the inputs. Consequently, the overall formulation sets up a procedure to predict the hyperparameters of this distribution which are then used to compute an objective function given training data. We demonstrate that this framework has the ability to provide for prediction confidence intervals based on the assumption of a probabilistic posterior, given an appropriate model architecture and adequate training data. The applicability of the present framework to cases with noisy measurements and limited observations is also assessed. To demonstrate the capabilities of this framework, we consider canonical regression problems of fluid dynamics from the viewpoint of reduced-order modeling and spatial data recovery for four canonical data sets. The examples considered in this study arise from (i) the shallow-water equations, (ii) a two-dimensional cylinder flow, (iii) the wake of a NACA0012 airfoil with a Gurney flap, and (iv) the NOAA sea surface temperature data set. Furthermore, the present results indicate that the probabilistic neural network not only produces a machine-learning-based fluid flow surrogate model but also systematically quantifies the uncertainty therein to assist with model interpretability.

42 ENGINEERING↗
DOE OSTI2017

Final Technical Report: The Incubation of Next-Generation Radar Technologies to Lower the Cost of Wind Energy

The National Wind Institute (NWI) at Texas Tech University (TTU) has had an impressive and well documented 46-year history of wind related research activities (http://www.depts.ttu.edu/nwi/). In 2011 with funding from the United States Department of Energy (DOE), an NWI team applied radar technologies and techniques to document the complex flows occurring across a wind plant. The resulting efforts yielded measurements that exceeded the capabilities of commercial lidar technologies with respect to maximum range, range resolution and scan speed. The NWI team was also the first to apply dual-Doppler synthesis and objective analysis techniques to resolve the full horizontal wind field (i.e. not just the line-of-sight wind speeds) to successfully define turbine inflow and wake flows across large segments of wind plants. While these successes advanced wind energy interests, the existing research radar platforms were designed to serve a diversity of meteorological applications, not specifically wind energy. Because of this broader focus and the design choices made during their development, the existing radars experienced technical limitations that inhibited their commercial viability and wide spread adoption. This DOE project enabled the development of a new radar prototype specifically designed for the purpose of documenting wind farm complex flows. Relative to other “off the shelf” radar technologies, the specialized transmitter and receiver chains were specifically designed to enhance data availability in non-precipitating atmospheres. The new radar prototype was integrated at TTU using components from various suppliers across the world, and installed at the Reese Technology Center in May 2016. Following installation, functionality and performance testing were completed, and subsequent comparative analysis indicated that the new prototype greatly enhances data availability by a factor of 3.5-50 in almost all atmospheric conditions. The new prototype also provided enhanced signal quality in clear air (i.e. non-precipitating) environments, mitigated atmospheric attenuation, and extended the useful range of data collection to beyond 30km in cooperative atmospheric conditions. Additionally, the new DOE-X prototype appears to benefit from Bragg scattering when the thermal stratification of the atmosphere is strong (i.e. nocturnal hours). This result was not possible in any capacity with the previous technology. Combined, these developments represent the achievement of all project objectives, advance the Technical Readiness Level (TRL) to a level of 7, and open the door for more widespread adoption and usage in the wind energy sector. At the same time, radar induced artifacts from multi-trip echoes and ground targets increased with the new technology, and these required additional attention for some applications. Commercialization activity accelerated in parallel with the DOE funded project, as SmartWind Technologies, L.L.C., was contracted to provide two new radar systems to DONG Energy to monitor the Westermost Rough wind plant off the east coast of the United Kingdom. These new early stage commercial radars systems were closely related to the DOE prototype, but maintain more robust ancillary support systems. The radars were installed during the summer of 2016, and have been operational since that time. Additionally, commercially funded advancements have since been made in processing sophistication to mitigate the previously identified radar artifacts. TTU and SmartWind Technologies stand ready to provide public and private partners focused on wind plant optimization with this new capability. Ancillary interests have also been identified as the initial deployments of the technology have shown the ability to identify and track avian and drone activity, opening up multi-purpose operational opportunities.

17 WIND ENERGY↗
DOE OSTI2023

A comparison of eight optimization methods applied to a wind farm layout optimization problem

Abstract. Selecting a wind farm layout optimization method is difficult. Comparisons between optimization methods in different papers can be uncertain due to the difficulty of exactly reproducing the objective function. Comparisons by just a few authors in one paper can be uncertain if the authors do not have experience using each algorithm. In this work we provide an algorithm comparison for a wind farm layout optimization case study between eight optimization methods applied, or directed, by researchers who developed those algorithms or who had other experience using them. We provided the objective function to each researcher to avoid ambiguity about relative performance due to a difference in objective function. While these comparisons are not perfect, we try to treat each algorithm more fairly by having researchers with experience using each algorithm apply each algorithm and by having a common objective function provided for analysis. The case study is from the International Energy Association (IEA) Wind Task 37, based on the Borssele III and IV wind farms with 81 turbines. Of particular interest in this case study is the presence of disconnected boundary regions and concave boundary features. The optimization methods studied represent a wide range of approaches, including gradient-free, gradient-based, and hybrid methods; discrete and continuous problem formulations; single-run and multi-start approaches; and mathematical and heuristic algorithms. We provide descriptions and references (where applicable) for each optimization method, as well as lists of pros and cons, to help readers determine an appropriate method for their use case. All the optimization methods perform similarly, with optimized wake loss values between 15.48 % and 15.70 % as compared to 17.28 % for the unoptimized provided layout. Each of the layouts found were different, but all layouts exhibited similar characteristics. Strong similarities across all the layouts include tightly packing wind turbines along the outer borders, loosely spacing turbines in the internal regions, and allocating similar numbers of turbines to each discrete boundary region. The best layout by annual energy production (AEP) was found using a new sequential allocation method, discrete exploration-based optimization (DEBO). Based on the results in this study, it appears that using an optimization algorithm can significantly improve wind farm performance, but there are many optimization methods that can perform well on the wind farm layout optimization problem, given that they are applied correctly.

17 WIND ENERGY↗
DOE OSTI2021

Reliability‐based layout optimization in offshore wind energy systems

Abstract Existing methods for optimizing wind array layouts typically use power or cost objectives and rarely consider reliability‐based objectives. Component and system failure rates, however, are dependent on location‐specific wind conditions, are influenced by array layout and wake interactions, and have a direct and significant impact on capital costs, operational costs, and power production. Although wind power plant models exist that calculate wind loads with sufficient resolution to capture component loading dynamics from wind conditions, they are computationally expensive and thus not suitable for research applications requiring many evaluations, particularly optimization. This study describes the development of computationally efficient, reliability‐based layout optimization methods, enabling us to explore the relationship between component reliability and layout optimization. These methods include the surrogate modeling of the planet bearing life based on varying wind conditions simulated in FAST.Farm and the formulation of reliability‐based objectives based on failure cost and power production models. Through demonstration of this method, we explore how wind conditions, objective functions, and capacity density influence reliability‐based layout optimization. Results indicate that considering reliability alongside power production can reduce failure costs associated with replacement costs and downtime while maintaining or improving power production. Our conclusions highlight the opportunity for wind power plant developers to integrate reliability and operational expenditures alongside performance and capital expenditure objectives in plant design and development to improve plant performance and costs.

17 WIND ENERGY↗
DOE OSTI2026

Sparsity Applications for Gradient‐Based Optimization of Wind Farms

Optimizing wind farms is essential for designing efficient energy systems, especially as farms grow larger and span multiple sites. However, this optimization becomes increasingly challenging due to the rising computational cost associated with more turbines. Gradient‐based optimization methods scale better than gradient‐free approaches for large problems, but the most computationally expensive component remains the calculation of gradients for the objective function and constraint Jacobians. To address this, we propose leveraging sparsity to accelerate gradient evaluations and reduce the size of the constraint Jacobian. Wind farms naturally exhibit sparsity—many turbines do not influence each other under certain wind directions. However, unlike traditional sparse problems with fixed patterns, wind farm sparsity is dynamic, requiring new strategies to handle changing interactions efficiently. This paper presents a study of sparsity in wind farm optimization and introduces several methods to exploit it. These strategies are tested on multiple farms using the analytic Cumulative Curl model, with gradients computed via automatic differentiation (AD). The same sparsity‐aware techniques are also applicable to finite difference (FD) methods, where they can yield even greater speedups due to the high cost of directional evaluations. Results show that sparse methods achieve up to a 10x speedup with less than ± 5% variance in optimized wake losses compared to traditional methods. These findings suggest that sparsity‐aware optimization not only maintains solution quality but also scales efficiently with farm size, enabling more comprehensive design exploration at reduced computational cost.

17 WIND ENERGY↗
DOE OSTI2019

Hard X-ray self-seeding commissioning at PAL-XFEL

A wake monochromator based on a large-area diamond single crystal for hard X-ray self-seeding has been successfully installed and commissioned in the hard X-ray free-electron laser (FEL) at the Pohang Accelerator Laboratory with international collaboration. For this commissioning, the self-seeding was demonstrated with a low bunch charge (40 pC) and the nominal bunch charge (180 pC) of self-amplified spontaneous emission (SASE) operation. The FEL pulse lengths were estimated as 7 fs and 29.5 fs, respectively. In both cases, the average spectral brightness increased by more than three times compared with the SASE mode. The self-seeding experiment was demonstrated for the first time using a crystal with a thickness of 30 µm, and a narrow bandwidth of 0.22 eV (full width at half-maximum) was obtained at 8.3 keV, which confirmed the functionality of a crystal with such a small thickness. In the nominal bunch-charge self-seeding experiment, the histogram of the intensity integrated over a 1 eV bandwidth showed a well defined Gaussian profile, which is evidence of the saturated FEL and a minimal electron-energy jitter (~1.2 × 10 –4 ) effect. Here, the corresponding low photon-energy jitter (~2.4 × 10 –4 ) of the SASE FEL pulse, which is two times lower than the Pierce parameter, enabled the seeding power to be maximized by maintaining the spectral overlap between SASE FEL gain and the monochromator.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Analysis of Narrow Bipolar Events Using Mode Decomposition Methods

Multi-resolution analysis methods can reveal the underlying physical dynamics of nonstationary signals, such as those from lightning. In this paper we demonstrate the application of two multi-resolution analysis methods: Ensemble Empirical Mode Decomposition (EEMD) and Variational Mode Decomposition (VMD) in a comparative way in the analysis of electric field change waveforms from lightning. EEMD and VMD decompose signals into a set of Intrinsic Mode Functions (IMFs). The IMFs can be combined using distance and divergence metrics to obtain noise reduction or to obtain new waveforms that isolate the physical processes of interest while removing irrelevant components of the original signal. We apply the EEMD and VMD methods to the observations of three close Narrow Bipolar Events (NBEs) that were reported by Rison et al. The ΔE observations reveal the occurrence of complex oscillatory processes after the main NBE sferic. We show that both EEMD and VMD are able to isolate the oscillations from the main NBE, with VMD being more effective of the two methods since it requires the least user supervision. The oscillations are found to begin at the end of the NBEs' downward fast positive breakdown and appear to be produced by a half-wavelength standing wave within a weakly-conducting resonant ionization cavity left behind in the wake of the streamer-based NBE event. In conclusion, additional analysis shows that one of the NBEs was likely initiated by an energetic cosmic ray shower, and also corrects a misinterpretation in the literature that fast breakdown is an artifact of NBE-like events in interferometer observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

SDSS-IV MaNGA IFS GALAXY SURVEY—SURVEY DESIGN, EXECUTION, AND INITIAL DATA QUALITY

The MaNGA Survey (Mapping Nearby Galaxies at Apache Point Observatory) is one of three core programs in the Sloan Digital Sky Survey IV. It is obtaining integral field spectroscopy for 10,000 nearby galaxies at a spectral resolution of R ∼ 2000 from 3622 to 10354 Å. The design of the survey is driven by a set of science requirements on the precision of estimates of the following properties: star formation rate surface density, gas metallicity, stellar population age, metallicity, and abundance ratio, and their gradients; stellar and gas kinematics; and enclosed gravitational mass as a function of radius. We describe how these science requirements set the depth of the observations and dictate sample selection. The majority of targeted galaxies are selected to ensure uniform spatial coverage in units of effective radius (R{sub e}) while maximizing spatial resolution. About two-thirds of the sample is covered out to 1.5 R{sub e} (Primary sample), and one-third of the sample is covered to 2.5 R{sub e} (Secondary sample). We describe the survey execution with details that would be useful in the design of similar future surveys. We also present statistics on the achieved data quality, specifically the point-spread function, sampling uniformity, spectral resolution, sky subtraction, and flux calibration. For our Primary sample, the median r -band signal-to-noise ratio is ∼70 per 1.4 Å pixel for spectra stacked between 1 R{sub e} and 1.5 R{sub e}. Measurements of various galaxy properties from the first-year data show that we are meeting or exceeding the defined requirements for the majority of our science goals.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Acceleration of on-axis and ring-shaped electron beams in wakefields driven by Laguerre-Gaussian pulses

The acceleration of electron beams with multiple transverse structures in wakefields driven by Laguerre-Gaussian pulses has been studied through three-dimensional (3D) particle-in-cell simulations. Under different laser-plasma conditions, the wakefield shows different transverse structures. In general cases, the wakefield shows a donut-like structure and it accelerates the ring-shaped hollow electron beam. When a lower plasma density or a smaller laser spot size is used, besides the donut-like wakefield, a central bell-like wakefield can also be excited. The wake sets in the center of the donut-like wake. In this case, both a central on-axis electron beam and a ring-shaped electron beam are simultaneously accelerated. Further, reducing the plasma density or laser spot size leads to an on-axis electron beam acceleration only. The research is beneficial for some potential applications requiring special pulse beam structures, such as positron acceleration and collimation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Generalised model of a sheath of a plasma bubble excited by a short laser pulse or by a relativistic electron bunch in transversely inhomogeneous plasma

An analytical model of a plasma bubble (a wake wave in the strongly nonlinear regime) in transversely inhomogeneous plasma is generalised to an arbitrary profile of an electron sheath at its boundary. Within the framework of this generalisation we have found the potential within the bubble and shown that its envelope is described by a second-order equation, similar to the equation of a less general theory. We have also determined the domain of parameters at which this equation is considerably simplified and no longer depends on the profile of the electron sheath. (extreme laser radiation: physics and fundamental applications)

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Robust wind farm layout optimization

Wake interactions in wind farms cause losses in annual energy production (AEP) on the order of 10%. Wind farm designers optimize the layout of the farm to mitigate wake losses, especially in the dominant site-specific wind directions. As wind turbines and wind farms grow in scale, optimization becomes more complex. Offshore wind farms regularly comprise more than 100 wind turbines and are characterized by complex boundaries due to shipping lanes, neighboring wind farms, and other constraints. Layout optimization methods are broadly split between gradient-based and gradient-free approaches. Gradient-based approaches can converge quickly and perform well for smaller, academic problems but are often sensitive to initial conditions and tuning parameters and require expert knowledge to use. On the other hand, gradient-free approaches can be more robust to problem complexities. We present a robust layout optimization approach based on a random search algorithm. The algorithm is intended for those who are not optimization experts and has few tuning parameters that need specification to achieve satisfactory results. Unlike off-the-shelf methods, which use generally available, non-domain-specific optimization routines that accept as inputs an optimization function and constraint definitions, this approach takes advantage of the relative computational costs of the different evaluations by evaluating cheaper computations first (boundary and minimum distance constraints) and running expensive AEP evaluations only if all other checks pass. Moreover, an outer genetic algorithm allows multiple solutions to evolve in parallel, enabling rapid solution development on high-performance computers. We discuss the relative ease of selecting necessary tuning parameters and demonstrate the efficacy of the genetic random search on a complex layout problem consisting of placing 70 turbines in a nonconvex and unconnected boundary region.

17 WIND ENERGY↗
DOE OSTI2016

Emerging activity in bilayered dispersions with wake-mediated interactions

In a bilayered system of particles with wake-mediated interactions, the action-reaction symmetry for the effective forces between particles of different layers is broken. Under quite general conditions we show that, if the interaction nonreciprocity exceeds a certain threshold, this creates an active dispersion of self-propelled clusters of Brownian particles. The emerging activity promotes unusual melting scenarios and an enormous diffusivity in the dense fluid. Furthermore, our results are obtained by computer simulation and analytical theory and can be verified in experiments with colloidal dispersions and complex plasmas.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Lead exposure is related to hypercortisolemic profiles and allostatic load in Brazilian older adults

Lead levels (Pb) have been linked to both hyper- and hypo-reactivity of hypothalamic-pituitary-adrenal axis (HPA) axis to acute stress in animals and humans. Similarly, allostatic load (AL), the ‘wear and tear’ of chronic stress, is associated with inadequate HPA axis activity. We examined whether Pb levels would be associated with altered diurnal cortisol profile, as a primary mediator of AL, during aging. Pb levels were measured from blood samples (BPb) of 126 Brazilian individuals (105 women), between 50 and 82 years old. Six neuroendocrine, metabolic, and anthropometric biomarkers were analyzed and values were transformed into an AL index using clinical reference cut-offs. Salivary samples were collected at home over 2 days at awakening, 30-min after waking, afternoon, and evening periods to determine cortisol levels. A multiple linear regression model showed a positive association between BPb as the independent continuous variable and cortisol awakening response (R{sup 2}=0.128; B=0.791; p=0.005) and overall cortisol concentration (R{sup 2}=0.266; B=0.889; p<0.001) as the outcomes. Repeated measures ANOVA showed that individuals with high BPb levels showed higher cortisol at 30 min after awakening (p=0.003), and in the afternoon (p=0.002) than those with low BPb values. Regarding AL, regression model showed that BPb was positively associated with AL index (R{sup 2}=0.100; B=0.204; p=0.032). Correlation analyzes with individual biomarkers showed that BPb was positively correlated with HDL cholesterol (p=0.02) and negatively correlated with DHEA-S (p=0.049). These findings suggest that Pb exposure, even at levels below the reference blood lead level for adults recommended by the National Institute for Occupational Safety and Health and by the Center for Disease Control and Prevention, may contribute to AL and dysregulated cortisol functioning in older adults. Considering these findings were based on cross-sectional data future research is needed to confirm our exploratory results. - Highlights: • Lead exposure is associated with several negative health outcomes. • Allostatic load (AL), the wear and tear of chronic stress, may be affected by lead exposure. • Lead concentration was associated with high cortisol levels and high allostatic load. • Even at very low levels of exposure, lead was associated with chronic stress mediators.

60 APPLIED LIFE SCIENCES↗