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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Potential landscape and flux field theory for turbulence and nonequilibrium fluid systems

Highlights: •The notion of nonequilibrium trinity based on detailed balance breaking is proposed. •Nonequilibrium trinity captures the nonequilibrium irreversible nature of turbulence. •Nonequilibrium trinity leads to the potential-flux form of stochastic fluid dynamics. •Energy flux in turbulence energy cascade is connected to nonequilibrium trinity. •The four-fifths law of turbulence is a manifestation of nonequilibrium trinity. -- Abstract: Turbulence is a paradigm for far-from-equilibrium systems without time reversal symmetry. To capture the nonequilibrium irreversible nature of turbulence and investigate its implications, we develop a potential landscape and flux field theory for turbulent flow and more general nonequilibrium fluid systems governed by stochastic Navier–Stokes equations. We find that equilibrium fluid systems with time reversibility are characterized by a detailed balance constraint that quantifies the detailed balance condition. In nonequilibrium fluid systems with nonequilibrium steady states, detailed balance breaking leads directly to a pair of interconnected consequences, namely, the non-Gaussian potential landscape and the irreversible probability flux, forming a ‘nonequilibrium trinity’. The nonequilibrium trinity characterizes the nonequilibrium irreversible essence of fluid systems with intrinsic time irreversibility and is manifested in various aspects of these systems. The nonequilibrium stochastic dynamics of fluid systems including turbulence with detailed balance breaking is shown to be driven by both the non-Gaussian potential landscape gradient and the irreversible probability flux, together with the reversible convective force and the stochastic stirring force. We reveal an underlying connection of the energy flux essential for turbulence energy cascade to the irreversible probability flux and the non-Gaussian potential landscape generated by detailed balance breaking. Using the energy flux as a center of connection, we demonstrate that the four-fifths law in fully developed turbulence is a consequence and reflection of the nonequilibrium trinity. We also show how the nonequilibrium trinity can affect the scaling laws in turbulence.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Data-driven, multi-moment fluid modeling of Landau damping

Deriving governing equations of complex physical systems based on first principles can be quite challenging when there are certain unknown terms and hidden physical mechanisms in the systems. In this work, we apply a deep learning architecture to learn fluid partial differential equations (PDEs) of a plasma system based on the data acquired from a fully kinetic model. Here, the learned multi-moment fluid PDEs are demonstrated to incorporate kinetic effect such as Landau damping. Based on the learned fluid closure, the data-driven, multi-moment fluid modeling can well reproduce all the physical quantities derived from the fully kinetic model. The calculated damping rate of Landau damping is consistent with both the fully kinetic simulation and the linear theory. The data-driven fluid modeling of PDEs for complex physical systems may be applied to improve the fluid closure and reduce the computational cost of multi-scale modeling of global systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Seismicity and fault aseismic deformation caused by fluid injection in decametric in-situ experiments

Seismicity induced by fluid perturbations became an important societal concern since felt earthquakes ( M w up to 6) occurred after anthropogenic activities. In order to mitigate the risks associated with undesired seismicity, as well as to be able to use the micro-seismicity as a probe for in-depth investigation of fluid-driven processes, it is of crucial importance to understand the links between seismicity, fluid pressure and flow. We have developed a series of in-situ, decameter-scale experiments of fault zone reactivation by controlled fluid injection, in order to improve the near-source geophysical and hydromechanical observations. The deployed geophysical monitoring close to the injection allows one to cover the full frequency range of the fault responses from the static deformation to the very high-frequency seismic emissions (up to 4 kHz). Here, we focus on the microseismicity ( M w ~ –4 to –3) recorded during two fluid injection experiments in low-permeable shale and highly-fractured limestone formations. In both experiments, the spatio-temporal distribution of the seismic events, the energy balance, and the seismic velocity changes of the fractured medium show that most of the deformation does not actually emit seismic signals. The induced deformation is mainly aseismic. Based on these high-resolution multiparametric observations in the near-field, we therefore proposed a new model for injection-induced seismicity: the seismicity is not directly induced by the increasing fluid pressure, but it is rather triggered by the stress perturbations transferred from the aseismic motion caused by the injection.

58 GEOSCIENCES↗
DOE OSTI2022

A level set approach for the computational study of a yield stress fluid filling a thin mold

Many important engineering and scientific applications such as cement slurries, foams, crude oil, and granular avalanches involve the concept of yield stress. Therefore, modeling yield stress fluids in different flow configurations, including the accurate prediction of the yield surface, is important. In this paper, we present a computational model based on the finite element method to study the flow of yield stress fluids in a thin mold and compare the results with data from flow visualization experiments. Here, we use the level set method to describe the interface between the filling fluid and air. We use polypropylene glycol as a model Newtonian fluid and Carbopol for the model yield stress fluid, as the Carbopol solution demonstrates yielding without thixotropy. To describe the yielding and shear-thinning behavior, we use a generalized Newtonian constitutive equation with a Bingham–Carreau–Yasuda form. We compare the results obtained from the mold filling experiments with the results from the three-dimensional (3D) model and from a reduced-order Hele-Shaw (HS) model that is two-dimensional, including the effect of shear-thinning along the thin direction only approximately. We show that both the 3D and the HS model can capture the experimental meniscus shape reasonably well for all the fluids considered at three different flow rates. This indicates that the shape evolution is insensitive to the dimensionality of the model. However, the viscosity and yield surfaces predicted by the 3D and HS models are different. The HS model underestimates the high viscosity and unyielded regions compared to the estimation by the 3D model.

42 ENGINEERING↗
DOE OSTI2019

The Effects of Earthquakes and Fluids on the Metamorphism of the Lower Continental Crust

Rock rheology and density have first-order effects on the lithosphere's response to plate tectonic forces at plate boundaries. Changes in these rock properties are controlled by metamorphic transformation processes that are critically dependent on the presence of fluids. At the onset of a continental collision, the lower crust is in most cases dry and strong. However, if exposed to internally produced or externally supplied fluids, the thickened crust will react and be converted into a mechanically weaker lithology by fluid-driven metamorphic reactions. Fluid introduction is often associated with deep crustal earthquakes. Microstructural evidence, suggest that in strong highly stressed rocks, seismic slip may be initiated by brittle deformation and that wall-rock damage caused by dynamic ruptures plays a very important role in allowing fluids to enter into contact with dry and highly reactive lower crustal rocks. The resulting metamorphism produces weaker rocks which subsequently deform by viscous creep. Volumes of weak rocks contained in a highly stressed environment of strong rocks may experience significant excursions toward higher pressure without any associated burial. Slow and highly localized creep processes in a velocity strengthening regime may produce mylonitic shear zones along faults initially characterized by earthquake-generated frictional melting and wall rock damage. However, stress pulses from earthquakes in the shallower brittle regime may kick start new episodes of seismic slip at velocity weakening conditions. These processes indicate that the evolution of the lower crust during continental collisions is controlled by the transient interplay between brittle deformation, fluid-rock interactions, and creep flow.

58 GEOSCIENCES↗
DOE OSTI2014

Determination of the thermodynamic correction factor of fluids confined in nano-metric slit pores from molecular simulation

The multi-component diffusive mass transport is generally quantified by means of the Maxwell-Stefan diffusion coefficients when using molecular simulations. These coefficients can be related to the Fick diffusion coefficients using the thermodynamic correction factor matrix, which requires to run several simulations to estimate all the elements of the matrix. In a recent work, Schnell et al. [“Thermodynamics of small systems embedded in a reservoir: A detailed analysis of finite size effects,” Mol. Phys. 110, 1069–1079 (2012)] developed an approach to determine the full matrix of thermodynamic factors from a single simulation in bulk. This approach relies on finite size effects of small systems on the density fluctuations. We present here an extension of their work for inhomogeneous Lennard Jones fluids confined in slit pores. We first verified this extension by cross validating the results obtained from this approach with the results obtained from the simulated adsorption isotherms, which allows to determine the thermodynamic factor in porous medium. We then studied the effects of the pore width (from 1 to 15 molecular sizes), of the solid-fluid interaction potential (Lennard Jones 9-3, hard wall potential) and of the reduced fluid density (from 0.1 to 0.7 at a reduced temperature T* = 2) on the thermodynamic factor. The deviation of the thermodynamic factor compared to its equivalent bulk value decreases when increasing the pore width and becomes insignificant for reduced pore width above 15. We also found that the thermodynamic factor is sensitive to the magnitude of the fluid-fluid and solid-fluid interactions, which softens or exacerbates the density fluctuations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Cosmology with moving bimetric fluids

We study cosmological implications of bigravity and massive gravity solutions with non-simultaneously diagonal metrics by considering the generalized Gordon and Kerr-Schild ansatzes. The scenario that we obtain is equivalent to that of General Relativity with additional non-comoving perfect fluids. We show that the most general ghost-free bimetric theory generates three kinds of effective fluids whose equations of state are fixed by a function of the ansatz. Different choices of such function allow to reproduce the behaviour of different dark fluids. In particular, the Gordon ansatz is suitable for the description of various kinds of slowly-moving fluids, whereas the Kerr-Schild one is shown to describe a null dark energy component. The motion of those dark fluids with respect to the CMB is shown to generate, in turn, a relative motion of baryonic matter with respect to radition which contributes to the CMB anisotropies. CMB dipole observations are able to set stringent limits on the dark sector described by the effective bimetric fluid.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Development of an Environmentally Acceptable Hydraulic Fluid

Hydroelectric plants operators like the United States Army Corps of Engineers seek their traditional petroleum-based fluids with environmentally acceptable hydraulic fluids (EAHF) to reduce their impact and liability related to spills and leakages to the water and environment. Artesion, Inc. and its sub-contractor Washington State University (WSU) sought to optimize WSU’s existing EAHF blend into an improved product that would demonstrate long-term stability while meeting the EAHF requirements of the EPA’s Vessel General Permit (VGP). Multiple rounds of Design of Experiments testing were performed from WSU’s base formulation, modifying mixing ratios to generate multiple test fluids. These fluids were then tested for hydraulic fluid properties. It was found that there was a significant tradeoff between oxidative stability and biodegradability; highly stable materials were not sufficiently biodegradable, while the highly biodegradable materials quickly failed in stability tests. After four rounds of Design of Experiments, AI and WSU had found a base fluid which met the VGP, but only had a Rotating Pressure Vessel Oxidative Test (RPVOT) of 284-minute RPVOT stability, far short of the 500-minute target that would be needed for hydroelectric plants. It was determined that WSU’s route had shown initial promise but needed more refinement to be able to produce an acceptable EAHF.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Systematic study on the phase transition of confined fluid mixture up to the critical region

Systematic experimental study on the phase transition of confined fluids up to the critical region has been performed, in which many new insights have been obtained. For confined pure fluids, compared to the bulk phase, the critical point shifts to lower pressure and temperature, but the relative shift of critical pressure is much larger than that of critical temperature. The behavior of the shift, i.e., the shift as a function of pore size, is dependent on the pore type. For confined fluid mixtures, compared to the bulk phase, the critical point also shifts to lower pressure and temperature, and the relative shift of critical pressure is also much larger than that of critical temperature. Confined fluid mixture behaves similarly to confined pure fluid, i.e., it exhibits hysteresis at lower temperature range and does not exhibit phase coexistence or phase envelope. An equation of state for confined pure fluids, based on the Generalized van der Waals partition function, has also been developed and demonstrated to accurately predict the capillary condensation of simple molecules in MCM-41. The parameters of the equation of state are derived from experimental critical point.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS1997

Effect of fluid ingestion on orthostatic responses following acute exercise

Orthostatic tolerance is impaired following an acute bout of exercise. This study examined the effect of fluid ingestion following treadmill exercise in restoring the cardiovascular responses to an orthostatic stress. Five men (age, 29.6 +/- 3.4 yrs) were exposed to a graded lower body negative (LBNP) pressure protocol (0 to -50 mmHg) during euhydration without exercise (C), 20 minutes after exercise dehydration (D), 20 minutes after exercise and fluid ingestion (FI20), and 60 minutes after exercise and fluid ingestion (FI60). Fluid ingestion (mean +/- SE) consisted of water-ingestion equivalent to 50% of the body weight lost during exercise (520 +/- 15 ml). Exercise dehydration resulted in significantly higher heart rates (119 +/- 8 vs 82 +/- 7 bpm), lower systolic blood pressures (95 +/- 1.7 vs 108 +/- 2.3 mmHg), a smaller increase in leg circumference (3.7 +/- 4 vs 6.9 +/- 1.0 mm), and an attenuated increase in total peripheral resistance (2.58 +/- 1.2 vs 4.28 +/- 0.9 mmHg/L/min) at -50 mmHg LBNP compared to the C condition. Fluid ingestion (both 20 and 60), partially restored the heart rate, systolic blood pressure, and total peripheral resistance responses to LBNP, but did not influence the change in leg circumference during LBNP (4 +/- 0.3 for R20 and 2.8 +/- 0.4 mm for R60). These data illustrate the effectiveness of fluid ingestion on improving orthostatic responses following exercise, and suggest that dehydration is a contributing factor to orthostatic intolerance following exercise.

NASA Center JSC↗
NASA NTRS2018

NASA Fluid Lensing & MiDAR: Next-Generation Remote Sensing Technologies for Aquatic Remote Sensing

We present two recent instrument technology developments at NASA, Fluid Lensing and MiDAR, and their application to remote sensing of Earth's aquatic systems. Fluid Lensing is the first remote sensing technology capable of imaging through ocean waves in 3D at sub-cm resolutions. MiDAR is a next-generation active hyperspectral remote sensing and optical communications instrument capable of active fluid lensing. Fluid Lensing has been used to provide 3D multispectral imagery of shallow marine systems from unmanned aerial vehicles (UAVs, or drones), including coral reefs in American Samoa and stromatolite reefs in Hamelin Pool, Western Australia. MiDAR is being deployed on aircraft and underwater remotely operated vehicles (ROVs) to enable a new method for remote sensing of living and nonliving structures in extreme environments. MiDAR images targets with high-intensity narrowband structured optical radiation to measure an objectâ€"TM"s non-linear spectral reflectance, image through fluid interfaces such as ocean waves with active fluid lensing, and simultaneously transmit high-bandwidth data. As an active instrument, MiDAR is capable of remotely sensing reflectance at the centimeter (cm) spatial scale with a signal-to-noise ratio (SNR) multiple orders of magnitude higher than passive airborne and spaceborne remote sensing systems with significantly reduced integration time. This allows for rapid video-frame-rate hyperspectral sensing into the far ultraviolet and VNIR wavelengths. Previously, MiDAR was developed into a TRL 2 laboratory instrument capable of imaging in thirty-two narrowband channels across the VNIR spectrum (400-950nm). Recently, MiDAR UV was raised to TRL4 and expanded to include five ultraviolet bands from 280-400nm, permitting UV remote sensing capabilities in UV A, B, and C bands and enabling mineral identification and stimulated fluorescence measurements of organic proteins and compounds, such as green fluorescent proteins in terrestrial and aquatic organics.

fluid lensing↗
NASA NTRSDate not supplied

Fluid System Stability Analysis Techniques

Fluid systems, or networks, consist of multiple components that work together to achieve some desired thermofluid state. For any generic application, this fluid state can be a combination of the fluid pressure, flow rate, enthalpy, or species concentration. Fluid system components, such as pumps and valves, are often governed by nonlinear differential equations, resulting in complex component-to-component interactions. System-level fluid network stability occurs when the flow through the system can maintain a steady-state solution in the presence of small perturbations, which depends on these component interactions. System instability, however, can go undetected until issues arise during integrated system testing. This presentation explores a method for system designers to think of the fluid network as an assembly of components, each with their own thermofluid surfaces of partial stability, called nullclines. The intersections of all nullclines yields system-level solutions, called equilibrium points. When designers define operating points, they are tuning system parameters so that these equilibrium points move to the desired location in the thermofluid state plane. However, linearization theory shows us that the dynamic behavior around these points can be unstable. The local stability of these equilibrium points can be assessed analytically with eigen-analysis, or numerically by propagating state-plane samples to construct a phase portrait. Investigating a phase portrait can help designers gain a qualitative understanding of a system’s dynamic performance. This understanding can then help inform requirement definitions, component selection, and operational procedures. This presentation includes an example of the phase portrait technique on a system featuring a centrifugal pump and a back-pressure regulator (BPR). Numerical modeling of this system suggests that equilibrium points on the left-hand side of the pump curve are dynamically unstable.

Fluid System↗
DOE OSTI2016

A Study of Physics-Informed Deep Learning for System Fluid Dynamics Closures

The sub-grid-scale (SGS) physics models, or so-called closure relations (CR), are essential in thermal-fluid modeling and simulation codes, ranging from large-eddy simulation to system-level thermo-fluid dynamic problems. While details vary, all thermo-fluid codes solve coupled mass-momentum-energy conservation partial differential equations (PDE). Traditionally, the analytical form of closure models has to be known, and then we calibrate the model using data from a set of applicable experiments. Characteristically, it takes long effort to gain insights and mechanistic understanding needed for developing closure models. Such a model is a compact form of data. The long time required for new model development limits the pace of model application while dealing with new geometries, new coolants or system conditions, particularly in newly designed systems. Alternative to mechanistic and semi-analytical models, it is possible to discover the pattern of closure relations by applying the modern machine learning methods to the body of relevant experimental data. Deep learning (DL) is a relatively new branch in the machine learning family, and a major breakthrough has been achieved since Hinton introduces a fast algorithm to efficiently train a feed-forward neural network (NN) with multilayer perceptrons. Generally, any NN with more than two layers is considered as deep learning, and it contains a large number of hyper-parameters to achieve pattern recognition or regression for complex datasets. Hornik shows that multilayer NN is compatible with universal approximation theorem. There is no constraint for a multilayer NN to capture the properties of any measurable information. This capability makes DL attractive for closure models in a system thermal-hydraulic code. As system geometry and/or operating conditions change, new physical experiments (increasingly sophisticated) are conducted to support evaluation and revision of closure models. Such a so-called data-driven modeling relaxes the structural form of system codes to directly assimilate data instead of hard-wiring the model to pre-calibrated correlations. The objective of this research is to enable cost-effective development of a DL-based closure that reflects the data. The previous work on applying machine learning techniques to fluid dynamics focused on statistical learning with basic NN from direct numerical simulations (DNS) dataset. In the present work, we show that DL-based closure models can cause the fluid calculation to diverge if multilayer NN is used. To address the issue, we investigate conditions by which the DL-based closure models work compatibly, stably, and effectively with PDE-constrained forward prediction problems. Optimally meeting the compatibility conditions constitutes a physics-informed deep learning (PIDL) strategy. We refer to this process as PDE-constrained machine learning or PDE-ML. To develop the technical basis for PDE-ML using DL-based fluid dynamics closure, numerical experiments are performed for manufactured problems of increasing complexity. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Tabulated Fluid Properties Research Report

The Multiphysics Object-Oriented Simulation Environment (MOOSE) enables a wide range of advanced nuclear reactor simulations.[6] Under the guidance of MOOSE’s Thermal Hydraulics Team,I worked to expand the capabilities of Tabulated Fluid Properties (TFP) in the fluid properties module. The fluid properties module allows the user to determine a variety of fluid properties by interpolating points between tabulated data. I implemented the ability to use bilinear interpolation instead of bicubic interpolation for interpolating tabulated data. I also changed the method of variable set inversions to use a 2-dimensional Newton’s Method utility that I created. Variable set inversions are often done from (v,e) to (p,T), where v is specific volume, e is specific internal energy, p is pressure and T is temperature. New routines have also been added into TFP such that it can be used with more applications, such as the Navier Stokes and Thermal Hydraulics modules in MOOSE for Pronghorn[5] and RELAP-7[1] respectively. This work was spurred by interest from NASA in testing a Nuclear Thermal Propulsion (NTP) engine system. NTP engines have drastically different fluid properties throughout the engine and Tabulated Fluid Properties provides the flexibility needed to properly simulate and test these engines.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

An adaptive lattice Boltzmann scheme for modeling two-fluid-phase flow in porous medium systems

In this paper, we formulate a multiple-relaxation-time (MRT) lattice-Boltzmann method (LBM) to simulate two-fluid-phase flow in porous medium systems. The MRT LBM is applied to simulate the displacement of a wetting fluid by a nonwetting fluid in a system corresponding to a microfluidic cell. Analysis of the simulation shows widely varying time scales for the dynamics of fluid pressures, fluid saturations, and interfacial curvatures that are typical characteristics of such systems. Displacement phenomena include Haines jumps, which are relatively short duration isolated events of rapid fluid displacement driven by capillary instability. An adaptive algorithm is advanced using a level-set method to locate interfaces and estimate their rate of advancement. Because the displacement dynamics are confined to the interfacial regions for a majority of the relaxation time, the computational effort is focused on these regions. The proposed algorithm is shown to reduce computational effort by an order of magnitude, while yielding essentially identical solutions to a conventional fully coupled approach. Finally, the challenges posed by Haines jumps are also resolved by the adaptive algorithm. Possible extensions to the advanced method are discussed.

42 ENGINEERING↗
DOE OSTI2015

Impact of drilling fluid rheology and wellbore pressure on rock cuttings removal performance: numerical investigation

Drilling fluids exhibit non-Newtonian behavior which is generally described in the literature by two rheological models: Power Law and Herschel-Bulkley models. We have used Eulerian- Eulerian multiphase flow model to evaluate the drilling fluid flow patterns and filter cake formation patterns for both models for ultra-deep drilling conditions. Simulated drilling fluid flow patterns clearly show that the Herschel - Bulkley model exhibits fewer vortices around the drilling pipe, indicating better rock cuttings removal performance. In addition to mud rheology, we have analyzed the pressure drop variation with the filter cake formation on the wellbore during ultradeep drilling process. We have shown that filter cake thickness at the wall linearly increases with differential pressure between the well and formation. This implies that the differential pressure needs to be optimized. Very thin filter cake may lead to excessive fluid seepage into the permeable subterranean vertical zone resulting in a loss of fluid circulation and hence in a loss of rock cuttings removal. Yet, very thick filter cake reduces the effective diameter of the hole which may lead to a poor rock cuttings removal performance and stuck pipe. The mathematical model presented here needs to be experimentally validated when filter cake thickness data in deep drilling conditions become available. The model could be useful to provide drilling engineers insight on the filter cake formation, drilling fluid flow pattern, and give guide-line to optimize the filter cake as field experimental data are scarce.

02 PETROLEUM↗
DOE OSTI2019

Neural network modeling of in situ fluid-filled pore size distributions in subsurface shale reservoirs under data constraints

Subsurface nuclear magnetic resonance (NMR) logs acquired in the wellbore environment are sensitive to fluid-filled pore size distribution, fluid mobility, permeability, and porosity in the near-wellbore reservoir volume. NMR response of a formation layer is processed to extract the T2 distribution, which approximates the fluid-filled pore size distribution. NMR logs are acquired in limited number of wells due to financial and operational challenges, which adversely affects reservoir characterization. We developed here two neural-network-based machine learning techniques, long short-term memory (LSTM) network and variational autoencoder with a convolutional layer (VAEc) network, to process the ‘easy-to-acquire’ formation mineral and fluid saturation logs to generate synthetic NMR T2 distributions in the absence of ‘hard-to-acquire’ NMR T2 distribution log. Both the predictive models are trained and tested on limited wireline log measurements randomly selected from a 300-ft depth interval of the Bakken shale formation. Synthesis performances of LSTM and VAEc models in terms of R 2 are 0.78 and 0.75, respectively. Noise is inevitable in logging data due to the complex wellbore and formation conditions. Notably, both the predictive models robustly synthesize the fluid-filled pore size distributions in the presence of 50% noise in input logs and 30% noise in training T2 data. The performance of the proposed methodology improves with access to larger volume of training data from other formation types. The proposed method is critical to the synthesis of in situ fluid-filled pore size distributions in shale formations under data constraints due to financial and operational challenges.

58 GEOSCIENCES↗
DOE OSTI2020

Assessment of the Utility of the Oral Fluid and Plasma Proteome for Hydrocodone Usage

Non-medical use and abuse of prescription opioids is a growing problem in both the civilian and military communities, with minimal technologies for detecting hydrocodone use. This study explored the proteomic changes that occur in the oral fluid and blood plasma following controlled hydrocodone administration in twenty subjects. The global proteomic profile was determined for samples taken at four time points per subject of pre-exposure and 4, 6, or 168 hours post-exposure. The oral fluid samples analyzed herein provided greater differentiation between “baseline” and “response” time points than was observed with blood plasma, at least partially due to significant person-to-person variability in the plasma proteome. A total of 399 proteins were identified from oral fluid samples, and the abundance of 102 of those proteins was determined to be significantly different upon metabolism of hydrocodone (4 and 6 hour time points) as compared to baseline levels in the oral fluid (pre-dose and 168 hour). This is the first, to our knowledge, assessment of the oral fluid and blood plasma proteome following hydrocodone administration, which demonstrates the potential of oral fluid as a non-invasive sample that may reveal features of hydrocodone or other opioid use and/or misuse.

Kaiser, Brooke LD↗