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At least 919 records · Page 51

Method for Hot Real-Time Sampling of Pyrolysis Vapors

Biomass Pyrolysis has been an increasing topic of research, in particular as a replacement for crude oil. This process utilizes moderate temperatures to thermally deconstruct the biomass which is then condensed into a mixture of liquid oxygenates to be used as fuel precursors. Pyrolysis oils contain more than 400 compounds, up to 60 percent of which do not re-volatilize for subsequent chemical analysis. Vapor chemical composition is also complicated as additional condensation reactions occur during the condensation and collection of the product. Due to the complexity of the pyrolysis oil, and a desire to catalytically upgrade the vapor composition before condensation, online real-time analytical techniques such as Molecular Beam Mass Spectrometry (MBMS) are of great use. However, in order to properly sample hot pyrolysis vapors, many challenges must be overcome. Sampling must occur within a narrow range of temperatures to reduce product composition changes from overheating or partial condensation or plugging of lines from condensed products. Residence times must be kept at a minimum to reduce further reaction chemistries. Pyrolysis vapors also form aerosols that are carried far downstream and can pass through filters resulting in build-up in downstream locations. The co-produced bio-char and ash from the pyrolysis process can lead to plugging of the sample lines, and must be filtered out at temperature, even with the use of cyclonic separators. A practical approach for considerations and sampling system design, as well as lessons learned are integrated into the hot analytical sampling system of the National Renewable Energy Laboratory's (NREL) Thermochemical Process Development Unit (TCPDU) to provide industrially relevant demonstrations of thermochemical transformations of biomass feedstocks at the pilot scale.

09 BIOMASS FUELS↗

Importance Sampling with Analog Scenarios for Stochastic Economic Dispatch

Increasing penetrations of renewable energy sources such as wind into power grids motivates the investigation of new approaches to 5-minute economic dispatch computation. In this poster, we investigate the application of importance sampling in the two-stage stochastic economic dispatch problem while using historical data to characterize uncertainty. In our numerical experiments, we observe that importance sampling performs better than the standard Monte Carlo sampling approach in preventing loss-of-load. While first-stage costs are comparable for both sampling methods, the second-stage costs are significantly reduced when the importance sampling method is employed.

97 MATHEMATICS AND COMPUTING↗

Sample Complexity of Power System State Estimation using Matrix Completion: Preprint

In this paper, we propose an analytical framework to quantify the amount of data samples needed to obtain accurate state estimation in a power system-a problem known as \emph{sample complexity} analysis in computer science. Motivated by the increasing adoption of distributed energy resources into the distribution-level grids, it becomes imperative to estimate the state of distribution grids in order to ensure stable operation. Traditional power system state estimation techniques mainly focus on the transmission network which involve solving an overdetermined system and eliminating bad data. However, distribution networks are typically \emph{underdetermined} due to the large number of connection points and high cost of pervasive installation of measurement devices. In this paper, we consider the recently proposed state-estimation method for underdetermined systems that is based on \emph{matrix completion}. In particular, a \emph{constrained} matrix completion algorithm was proposed, wherein the standard matrix completion problem is augmented with additional equality constraints representing the physics (namely power-flow constraints). We analyze the sample complexity of this general method by proving an upper bound on the sample complexity that depends directly on the properties of these constraints that can lower number of needed samples as compared to the unconstrained problem. To demonstrate the improvement that the constraints add to state estimation, we test the method on a 141-bus distribution network case study and compare it to the traditional least squares minimization state estimation method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

An Efficient Sampling-Based Method for Sensitivity and Uncertainty Analysis Through RAVEN

Sensitivity analysis (SA) and uncertainty quantification (UQ) are now widely recognized as essential parts of analyses for complex nuclear systems. Plenty of well-established methodologies are already available for performing SA and UQ, such as Monte Carlo analysis, adjoint-based method, and variance decomposition. The focus of this summary is on developing an efficient sampling-based approach to perform SA and UQ through RAVEN. RAVEN (Risk Analysis and Virtual control Environment) is a software framework able to perform SA and UQ, currently under development at the Idaho National Laboratory. In literature, a number of approaches have been developed to accelerate the process of SA and UQ for large complex systems, such as principal component analysis (PCA) of input space, input-output correlation analysis, and intersection subspace methods. The fundamental idea is to identify the dominant active directions in the parameter space prior to conducting SA and UQ. The premise is that the number of active directions is much less than the dimensionality of input space. In this work, the PCA or Karhunen-Loeve expansion or SVD method is implemented in RAVEN to identify the active directions. This approach is also combined with the forward sampling approaches, such as Monte Carlo, Grid, Latin Hypercube, and Response Surface Design sampling approaches that are currently available in RAVEN, to perform SA and UQ more efficiently. The summary is organized as follows. In the following section, we present the PCA-based forward sampling approach. The effectiveness and efficiency are discussed in the numerical results section. The paper then ends with a concluding summary. In this summary, we have presented PCA-based forward sampling approach to perform SA and UQ. The goal is to reduce the computational overhead for repetitive executions of complex nuclear systems that are generally required when performing SA and UQ. The control of correlations between input parameters is implemented in RAVEN to better represent the input relationships. In addition, we are currently examining our implementations with more realistic models, and we are also focusing on implementation of some new high-dimensional input reduction techniques in RAVEN. (authors)

97 MATHEMATICS AND COMPUTING↗

Improvement of Drop‐Hammer Impact Testing for Safety Assessment of High Explosives Using 10‐mg Samples

Here, in this study, we established an improved method for drop-hammer impact testing of small quantities of high explosives (10 mg). We performed about seven hundred impact tests under various experimental conditions (e.g., sandpaper vs bare anvil, different sample masses, drop-weights, and striker diameters) to determine an optimal set of conditions and reaction detection methods (e.g., gas analysis, video, and sound recordings) that give the most statistically reliable results with 10 mg samples. We used both Frequentist and Bayesian statistical approaches to compare estimates of the drop height (DH50) that initiates a reaction 50% of the time, and to quantify the associated uncertainty. Gas analysis proved to be the most reliable reaction detection method, showing unambiguous rises in HE decomposition products (e.g., CO 2 ) even when the other indicators (e.g., sound, video) were inconclusive. The impact tests performed with a bare anvil showed much better reproducibility than those conducted with sandpaper, reducing the largest uncertainty observed in the data sets by a factor of 1.7. The DH 50 values obtained from three different sample masses (10, 20, and 35 mg) fell within the uncertainties of the measurements. We demonstrated the improved procedure (i.e., 10-mg samples, gas analysis, bare anvil, and Bayesian approach) on a variety of PETN samples having different surface areas and thermal histories.

PETN↗

Fukushima Daiichi reactor source term attribution using cesium isotope ratios from contaminated environmental samples

Source term attribution of environmental contamination following the Fukushima Daiichi Nuclear Power Plant (FDNPP) disaster is complicated by a large number of possible similar emission source terms (e.g. FDNPP reactor cores 1–3 and spent fuel ponds 1–4). Cesium isotopic analyses can be utilized to discriminate between environmental contamination from different FDNPP source terms and, if samples are sufficiently temporally resolved, potentially provide insights into the extent of reactor core damage at a given time. In this work, rice, soil, mushroom, and soybean samples taken 100–250 km from the FDNPP site were dissolved using microwave digestion. Radiocesium was extracted and purified using two sequential ammonium molybdophosphate-polyacrylonitrile columns, following which 135 Cs/ 137 Cs isotope ratios were measured using thermal ionization mass spectrometry (TIMS). Results were compared with data reported previously from locations to the northwest of FDNPP and 30 km to the south of FDNPP. 135 Cs/ 137 Cs isotope ratios from samples 100–250 km to the southwest of the FDNPP site show a consistent value of 0.376 ± 0.008. 135 Cs/ 137 Cs versus 134 Cs/ 137 Cs correlation plots suggest that radiocesium to the southwest is derived from a mixture of FDNPP reactor cores 1, 2, and 3. Conclusions from the cesium isotopic data are in agreement with those derived independently based upon the event chronology combined with meteorological conditions at the time of the disaster. In conclusion, cesium isotopic analyses provide a powerful tool for source term discrimination of environmental radiocesium contamination at the FDNPP site. For higher precision source term attribution and forensic determination of the FDNPP core conditions based upon cesium, analyses of a larger number of samples from locations to the north and south of the FDNPP site (particularly time-resolved air filter samples) are needed. Published in 2016. This article is a U.S. Government work and is in the public domain in the USA.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

ToF-SIMS Depth Profiling Of Insulating Samples, Interlaced Mode Or Non-interlaced Mode?

Dual beam depth profiling strategy has been widely adopted in ToF-SIMS depth profiling, in which two basic operation modes, interlaced mode and non-interlaced mode, are commonly used. Generally, interlaced mode is recommended for conductive or semi-conductive samples, whereas non-interlaced mode is recommended for insulating samples, where charge compensation can be an issue. Recent publications, however, show that the interlaced mode can be used effectively for glass depth profiling, despite the fact that glass is an insulator. In this study, we provide a simple guide for choosing between interlaced mode and non-interlaced mode for insulator depth profiling. Two representative cases are presented: (1) depth profiling of a leached glass sample, and (2) depth profiling of a single crystal MgO sample. In brief, the interlaced mode should be attempted first, because (1) it may provide reasonable-quality data, and (2) it is time-saving for most cases, and (3) it introduces low H/C/O background. If data quality is the top priority and measurement time is flexible, non-interlaced mode is recommended because interlaced mode may suffer from low signal intensity and poor mass resolution. A big challenge is tracking trace H/C/O in a highly insulating sample (e.g., MgO), because non-interlaced mode may introduce strong H/C/O background but interlaced mode may suffer from low signal intensity. Meanwhile, a C or Au coating is found to be very effective to improve the signal intensity. Surprisingly, the best analyzing location is not on the C or Au coating, but at the edge (outside) of the coating.

Environmental Molecular Sciences Laboratory↗

Sample size estimation for case‐crossover studies

Case‐crossover study designs are observational studies used to assess postmarket safety of medical products (eg, vaccines or drugs). As a case‐crossover study is self‐controlled, its advantages include better control for confounding because the design controls for any time‐invariant measured and unmeasured confounding and potentially greater feasibility as only data from those experiencing an event (or cases) are required. However, self‐matching also introduces correlation between case and control periods within a subject or matched unit. To estimate sample size in a case‐crossover study, investigators currently use Dupont's formula ( Biometrics 1988; 43 :1157‐1168), which was originally developed for a matched case‐control study. This formula is relevant as it takes into account correlation in exposure between controls and cases, which are expected to be high in self‐controlled studies. However, in our study, we show that Dupont's formula and other currently used methods to determine sample size for case‐crossover studies may be inadequate. Specifically, these formulas tend to underestimate the true required sample size, determined through simulations, for a range of values in the parameter space. We present mathematical derivations to explain where some currently used methods fail and propose two new sample size estimation methods that provide a more accurate estimate of the true required sample size.

Dharmarajan, Sai↗

Robust surfactant-assisted one-pot sample preparation for label-free single-cell and nanoscale proteomics

With advanced mass spectrometry (MS)-based proteomics, genome-scale proteome coverage can be achieved from bulk cells. However, such bulk measurement obscures cell to cell heterogeneity, precluding proteome profiling of single cells and small numbers of cells of interest. To address this issue, in recent 5 years there are a surge of small sample preparation methods developed for robust effective collection and processing of single cells and small numbers of cells for in-depth MS-based proteome profiling. Based on their broad accessibility, they can be categorized into two types: specific device- and standard PCR tube- or multi-well plate-based methods. Herein we describe the detailed protocol of our recently developed, easily adoptable, Surfactant-assisted One-Pot (SOP) sample preparation coupled with MS method termed SOP-MS for label-free single-cell and nanoscale proteomics. SOP-MS capitalizes on the combination of a MS-compatible surfactant, DDM (n-Dodecyl-ß-D-maltoside), and standard low-bind PCR tube or multi-well plate for ‘all-in-one’ one-pot sample preparation without sample transfer. With its robust and convenient features, SOP-MS can be readily implemented in any MS laboratory for single-cell and nanoscale proteomics. With further improvements in MS detection sensitivity and sample throughput, we believe that SOP-MS could open an avenue for single-cell proteomics with broad applicability in the biological and biomedical research.

Single-cell proteomics, nanoscale proteomics, SOP-↗

Convergence and Efficiency of Adaptive Importance Sampling Techniques with Partial Biasing

We propose a new Monte Carlo method to efficiently sample a multimodal distribution (known up to a normalization constant). We consider a generalization of the discrete-time Self Healing Umbrella Sampling method, which can also be seen as a generalization of well-tempered metadynamics. The dynamics is based on an adaptive importance technique. The importance function relies on the weights (namely the relative probabilities) of disjoint sets which form a partition of the space. These weights are unknown but are learnt on the fly yielding an adaptive algorithm. In the context of computational statistical physics, the logarithm of these weights is, up to an additive constant, the free-energy, and the discrete valued function defining the partition is called the collective variable. The algorithm falls into the general class of Wang–Landau type methods, and is a generalization of the original Self Healing Umbrella Sampling method in two ways: (i) the updating strategy leads to a larger penalization strength of already visited sets in order to escape more quickly from metastable states, and (ii) the target distribution is biased using only a fraction of the free-energy, in order to increase the effective sample size and reduce the variance of importance sampling estimators. We prove the convergence of the algorithm and analyze numerically its efficiency on a toy example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Rapid Determination Of Radiostrontium In Large Soil Samples

A new method for the determination of radiostrontium in large soil samples has been developed at the Savannah River Environmental Laboratory (Aiken, SC, USA) that allows rapid preconcentration and separation of strontium in large soil samples for the measurement of strontium isotopes by gas flow proportional counting. The need for rapid analyses in the event of a Radiological Dispersive Device (RDD) or Improvised Nuclear Device (IND) event is well-known. In addition, the recent accident at Fukushima Nuclear Power Plant in March, 2011 reinforces the need to have rapid analyses for radionuclides in environmental samples in the event of a nuclear accident. The method employs a novel pre-concentration step that utilizes an iron hydroxide precipitation (enhanced with calcium phosphate) followed by a final calcium fluoride precipitation to remove silicates and other matrix components. The pre-concentration steps, in combination with a rapid Sr Resin separation using vacuum box technology, allow very large soil samples to be analyzed for {sup 89,90}Sr using gas flow proportional counting with a lower method detection limit. The calcium fluoride precipitation eliminates column flow problems typically associated with large amounts of silicates in large soil samples.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Rapid fusion method for the determination of Pu, Np, and Am in large soil samples

A new rapid sodium hydroxide fusion method for the preparation of 10-20 g soil samples has been developed by the Savannah River National Laboratory (SRNL). The method enables lower detection limits for plutonium, neptunium, and americium in environmental soil samples. The method also significantly reduces sample processing time and acid fume generation compared to traditional soil digestion techniques using hydrofluoric acid. Ten gram soil aliquots can be ashed and fused using the new method in 1-2 hours, completely dissolving samples, including refractory particles. Pu, Np and Am are separated using stacked 2mL cartridges of TEVA and DGA Resin and measured using alpha spectrometry. The method can be adapted for measurement by inductively-coupled plasma mass spectrometry (ICP-MS). Two 10 g soil aliquots of fused soil may be combined prior to chromatographic separations to further improve detection limits. Total sample preparation time, including chromatographic separations and alpha spectrometry source preparation, is less than 8 hours.

54 ENVIRONMENTAL SCIENCES↗

Rapid method to determine actinides and 89/90 Sr in limestone and marble samples

A new method for the determination of actinides and radiostrontium in limestone and marble samples has been developed that utilizes a rapid sodium hydroxide fusion to digest the sample. Following rapid pre-concentration steps to remove sample matrix interferences, the actinides and 89/90 Sr are separated using extraction chromatographic resins and measured radiometrically. The advantages of sodium hydroxide fusion versus other fusion techniques will be discussed. Lastly, this approach has a sample preparation time for limestone and marble samples of <4 hours.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Theoretical realization of three-dimensional nanolattice structure fabrication based on high-order waveguide-mode interference and sample rotation

A theoretical method of using high-order waveguide-mode interference combined with sample rotation is proposed to fabricate different kinds of three-dimensional nanolattice structures. The lithography sample is assisted by an asymmetric metal-cladding dielectric waveguide structure. High-order waveguide modes can be excited in the photoresist layer by both transverse magnetic and transverse electric polarized light. By utilizing multiple exposures of high-order waveguide-mode interference combined with sample-rotation, various three-dimensional nanolattice structures can be obtained. The resulting optical field distributions are simulated using the finite element method in this study, and sample rotation is expressed by coordinate matrix transformation. As examples, the three-dimensional optical field distributions resulting from fifth-order waveguide-mode interference were simulated with 90° and 60° sample rotations and multiple exposures. The results show that a quasi-cuboid structure with a simple tetragonal arrangement and a quasi-hexagonal structure with a hexagonal close-packed lattice can be obtained. Moreover, the numerical simulation results revealed that the shapes, sizes, arrangements, and periods of the structures can be controlled by the rotation method, photoresist thickness, waveguide modes used for exposure, and so on.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Evaluation of dried blood spot sampling for verification of exposure to chemical threat agents

Abstract Purpose Exposure to chemical threat agents (CTAs), including nerve agents, the vesicating agent sulfur mustard, and opioids, remains a significant threat to warfighter and civilian populations. Definitive analytical methods to verify exposure to CTAs require shipping refrigerated or frozen biomedical samples to reference laboratories for analysis. Logistical and financial burdens arise as the transport of biomedical samples is subject to strict restrictions and complex packaging, which, if done incorrectly, can lead to sample deterioration. The use of dried blood spot (DBS) sampling could provide operational improvements for collecting, storing, and shipping important forensic samples. Therefore, this effort focuses on developing DBS techniques with Mitra® 30-µL volumetric absorptive microsampling (VAMS®) devices for use in CTA exposure verification. Methods VAMS® devices were loaded and dried with human whole blood that was exposed to the metabolites pinacolyl methylphosphonic acid (PMPA), ethyl methylphosphonic acid (EMPA), 1,1’sulfonylbis[2-(methylsulfinyl)ethane] (SBMSE), norfentanyl, norcarfentanil, norsufentanil, and norlofentanil. Following extraction from the VAMS® devices, metabolites were detected using liquid chromatography-tandem mass spectrometry (LC–MS/MS). The methods were validated for performance by assessing sensitivity, precision, accuracy, and recovery. Results These methods were sensitive to 1 ng/mL for SBMSE, 0.5 ng/mL for PMPA, EMPA, and norfentanyl; 0.1 ng/mL for norlofentanil, and 0.05 ng/mL for norsufentanil and norcarfentanil. All methods met acceptable precision and accuracy criteria with favorable recovery. Conclusions These results demonstrated the utility of VAMS® in stabilizing human whole blood and show promise as an improved collection method for verification of exposure to various CTAs.

Toxicology↗

Colloidal gold nanoparticle probe-based immunochromatographic assay for the rapid detection of chromium ions in water and serum samples

An immunochromatographic assay (ICA) using gold nanoparticles coated with monoclonal antibody (McAb) for the detection of chromium ions (Cr) in water and serum samples was developed, optimized, and validated. Gold nanoparticles coated with affinity- purified monoclonal antibodies against isothiocyanobenzyl-EDTA (iEDTA)-chelated Cr3+ were used as the detecting reagent in this completive immunoassay-based one- step test strip. The ICA was investigated to measure chromium speciation in water samples. Chromium standard samples of 0-80 ng/mL in water were determined by the test strips. The results showed that the visual lowest detection limit (LDL) of the test strip was 50.0 ng/mL. A portable colorimetric lateral flow reader was used for the quantification of Cr. The results indicated that the linear range of the ICA with colorimetric detection was 5-80 ng/mL. The ICA was also validated for the detection of chromium ions in serum samples. The test trips showed high stability in that they could be stored at at 37 C for at least 12 weeks without significant loss of activity. The test strip also showed good selectivity for Cr detection with negligible interference from other heavy metals. Because of its low cost and short testing time (within 5 min), the test strip is especially suitable for on-site large- scale screening of Cr-polluted water samples, biomonitoring of Cr exposure, and many other field applications.

74 ATOMIC AND MOLECULAR PHYSICS↗

Effects of mechanical stress and vitreous samples in retinal pigment epithelial cells

In rhegmatogenous retinal detachment (RRD), scattered RPE cells from the basement membrane into the vitreous cavity undergo an epithelial mesenchymal transition (EMT) and form the intraocular fibrous membrane in response to vitreous fluid. We investigated whether exposure to vitreous samples was associated with EMT-associated signals and mesenchymal characters. Human vitreous samples were collected from patients with RRD, epiretinal membrane (ERM), or macular hole (MH). We evaluated the effects of vitreous on ARPE-19 cells in suspension cultures using poly 2-hydroxyethyl methacrylate-coated dishes and three-dimensional (3D) Matrigel cultures. We found that exposure to vitreous samples did not induce morphological changes or accelerate wound closure in monolayers. Several samples showed increased phosphorylation of Smad2 and nuclear translocation of nuclear factor-κB. Mechanical stress triggered an elevation of phosphorylation levels in Smad2. In addition, exposure to vitreous fluid increased the phosphorylation of p38 mitogen-activated protein kinase in cell suspension cultures after mechanical stress. Moreover, ARPE-19 cells showed a stellate invasive phenotype in 3D Matrigel cultures with vitreous samples. In this study, we demonstrated that mechanical stress and vitreous were associated with EMT-associated signals and invasive phenotypes in 3D cultures but not in monolayers. These results have important implications for the role of vitreous humor in the induction of EMT and intraocular fibrosis.

60 APPLIED LIFE SCIENCES↗

Effective detection of CO 2 leakage: a comparison of groundwater sampling and pressure monitoring

Shallow aquifer monitoring is likely to be a required aspect to any geologic CO 2 sequestration operation. Collecting groundwater samples and analyzing for geochemical parameters such as pH, alkalinity, total dissolved carbon, and trace metals has been suggested by a number of authors as a possible strategy to detect CO 2 leakage. The effectiveness of this approach, however, will depend on the hydrodynamics of the leak-induced CO 2 plume and the spatial distribution of the monitoring wells relative to the origin of the leak. To our knowledge, the expected effectiveness of groundwater sampling to detect CO 2 leakage has not yet been quantitatively assessed. In this study we query hundreds of simulations developed for the National Risk Assessment Project (US DOE) to estimate risks to drinking water resources associated with CO 2 leaks. The ensemble of simulations represent transient, 3-D multi-phase reactive transport of CO 2 and brine leaked from a sequestration reservoir, via a leaky wellbore, into an unconfined aquifer. Key characteristics of the aquifer, including thickness, mean permeability, background hydraulic gradient, and geostatistical measures of aquifer heterogeneity, were all considered uncertain parameters. Complex temporally-varying CO 2 and brine leak rate scenarios were simulated using a heuristic scheme with ten uncertain parameters. The simulations collectively predict the spatial and temporal evolution of CO 2 and brine plumes over 200 years in a shallow aquifer under a wide range of leakage scenarios and aquifer characteristics. Using spatial data from an existing network of shallow drinking water wells in the Edwards Aquifer, TX, as one illustrative example, we calculated the likelihood of leakage detection by groundwater sampling. In this monitoring example, there are 128 wells available for sampling, with a density of about 2.6 wells per square kilometer. If the location of the leak is unknown a priori, a reasonable assumption in many cases, we found that the leak would be detected in at least one of the monitoring wells in less than 10% of the scenarios considered. This is because plume sizes are relatively small, and so the probability of detection decreases rapidly with distance from the leakage point. For example, 400m away from the leakage point there is less than 20% chance of detection. We then compared the effectiveness of groundwater quality sampling to shallow aquifer and/or reservoir pressure monitoring. For the Edwards Aquifer example, pressure monitoring in the same monitoring well network was found to be even less effective that groundwater quality monitoring. This is presumably due to the unconfined conditions and relatively high permeability, so pressure perturbations quickly dissipate. Although specific results may differ from site to site, this type of analysis should be useful to site operators and regulators when selecting leak detection strategies. Given the spatial characteristics of a proposed monitoring well network, probabilities of leakage detection can be rapidly calculated using this methodology. Although conditions such as these may not be favorable for leakage detection in shallow aquifers, leakage detection could be much more successful in the injection reservoir. We demonstrate proof-of-concept for this hypothesis, presenting a simulation where there is measurable pressure change at the injection well due to overpressurization, fault rupture, and consequent leakage up the fault into intermediate and shallow aquifers. The size of the detectible pressure change footprint is much larger in the reservoir than in either of the overlying aquifers. Further exploration of the range of conditions for which this technique would be successful is the topic of current study.

54 ENVIRONMENTAL SCIENCES↗