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On September 16, 2021 the Idaho National Laboratory shipped a Battelle Research Reactor (BRR) cask loaded with five Nuclear Science User Facilities (NSUF) experiments and one Accident Tolerant Fuels (ATF) experiment from the Advanced Test Reactor (ATR) to the Hot Fuel Examination Facility (HFEF) at the INL Materials and Fuels Complex (MFC) for post-irradiation examination.
This paper presents a cyber-physical testbed, developed to investigate the complex interactions between emerging microgrid technologies such as grid-interactive power sources, control systems, and a wide variety of communication platforms and bandwidths. The cyber-physical testbed consists of three major components for testing and validation: real time models of a distribution feeder model with microgrid assets that are integrated into the National Renewable Energy Laboratory's (NREL) power hardware-in-the-loop (PHIL) platform; real-time capable network-simulator-in-the-loop (NSIL) models; and physical hardware including inverters and a simple system controller. Several load profiles and microgrid configurations were tested to examine the effect on system performance with increasing channel delays and router processing delays in the network simulator. Testing demonstrated that the controller's ability to maintain a target grid import power band was severely diminished with increasing network delays and laid the foundation for future testing of more complex cyber-physical systems.
The Delivery Environments Testbeds to Reduce Uncertainty in Simulations and Tests (TRUST) project is a broad project intended to analyze simplified problems experimentally and with modeling and simulation. The purpose of analyzing these simplified problems is to extend solution methods to more complex problems, as well as understand deficiencies and gaps in knowledge of methods currently used in more complex analyses. The TRUST project encompasses several smaller testbeds intended to isolate individual phenomena. The testbed under consideration in this report is the Sensors in Environments: Thermocouples testbed. In previous years, the purpose of this testbed was to quantify uncertainty of thermocouple sensors. To accomplish this, an aluminum plate was placed in a thermal chamber and subject to various types of thermal loading. Thermocouples were placed in various locations on the aluminum plate in various configurations (e.g., embedded in the plate, placed under Kapton tape), and an effort was made to quantify uncertainty in these measurements. Finite element simulations were performed to investigate how sensitive these measurements were to parameters such as the boundary conditions on the plate and material properties. However, a fundamental source of uncertainty in this analysis was the convective heat transfer from the plate. Convective heat transfer is a complex physical phenomenon comprised of a number of interacting sub-processes and is difficult to predict accurately a priori. As such, the main purpose of this testbed in FY25 was to better understand, both experimentally and numerically, the convective heat transfer from the plate. This is a highly applicable problem to several more complex problems, as convective heat transfer occurs in nearly all problems where a body is moving through air. Numerically, this required a two-step approach. First, the air flow in the thermal chamber was in vestigated using computational fluid dynamics. The commercial solver Fluent was used to perform these simulations. From these simulations, a heat transfer coefficient over the surface of the plate was calculated. This heat transfer was then used as boundary conditions for finite element heat transfer simulations within the plate, which were performed using Abaqus. Significant effort was devoted to automating the handoff between these two solvers. Experimentally, previous thermocouple results in the plate were used to validate the time-dependent thermal profiles produced from Abaqus. Further experimental efforts were performed both to help validate the Fluent simulations and to inform its boundary conditions. For example, hot-wire anemometers were used to measure the velocity in the chamber, which would be particularly useful in understanding the chamber inlet velocity. Thermocouple measurements were also taken in the chamber, instead of only on the plate, to serve as validation evidence for the Fluent simulations. Numerical results showed that the Fluent to Abaqus workflow matched previous plate thermocouple measurements well. This type of handoff is useful for more complex experiments, or those that are not able to be examined in as great of detail as this testbed, as it was performed without any experimental input. Experimental results, however, were more mixed. The anemometers proved unreliable, with inconsistent measurements across all anemometers, even at locations that were nearly identical. On the other hand, the thermocouples provided a relatively rich view of the temperature field in the chamber.
Here, unintended radiated emissions (URE) from electronic devices are conducted on to the power infrastructure and can be collected and analyzed for non-intrusive load monitoring (NILM) applications. Dimensionally aligned signal projections (DASP) were previously introduced as specialized signal transforms to enable device classification using machine learning on statistical features derived from the DASP transforms. In this work, we explore multi-device classification which requires more sophisticated methods owing to the complexity of the feature space such as large dynamic range, non-contiguous features, over-lapping features, and nonlinear interactions of features. In particular, we introduce an additional DASP algorithm for increased resolution and sensitivity to intermodulation products and examine the utility of convolutional neural networks (CNNs) to extract and learn features directly from DASP images for classification of single and multiple device URE captures.
This paper presents a nonlinear analytical model of a novel double sided flux concentrating Transverse Flux Machine (TFM) based on the Magnetic Equivalent Circuit (MEC) model. The analytical model uses a series-parallel combination of flux tubes to predict the flux paths through different parts of the machine including air gaps, permanent magnets (PM), stator, and rotor. The two-dimensional MEC model approximates the complex three-dimensional flux paths of the TFM and includes the effects of magnetic saturation. The model is capable of adapting to any geometry which makes it a good alternative for evaluating prospective designs of TFM as compared to finite element solvers which are numerically intensive and require more computation time. A single phase, 1 kW, 400 rpm machine is analytically modeled and its resulting flux distribution, no-load EMF and torque, verified with Finite Element Analysis (FEA). The results are found to be in agreement with less than 5% error, while reducing the computation time by 25 times.
Research on extraction of uranium from seawater has been active in recent years because this technology can provide an additional supply of uranium for nuclear fuel from a much larger uranium reservoir (the oceans) and the processes are more environment friendly. One critical challenge of the development of this technology is to make uranium adsorbents perform well not just in the oversimplified laboratory system (e.g. artificial seawater) but also in the complex real seawater matrix, which is comprised of many competing ions and natural organic substances. Here, we conducted a systematic study using a continuous-flow seawater flume system to assess the potential impacts of dissolved organic matter (DOM) and dissolved iron on the uranium uptake performance (including adsorbent reusability) of amidoxime-based adsorbents. In the 28-day exposure, the adsorbent exposed in dissolved Fe-spiked seawater (low DOM/high Fe) and humic acid-spiked seawater (high DOM/high Fe) showed lower uranium adsorption loadings (73% and 56% of adsorption loading, respectively) than the same adsorbent exposed in seawater without spiking (low DOM/low Fe). Interestingly, the uranium adsorption loading of the reused adsorbent (after uranium stripping by a mild bicarbonate elution) in the dissolved Fe-spiked seawater dropped substantially to only 24% of the loading in the unspiked clean seawater counterpart; while not much change was observed in the performance of adsorbent exposed to the humic acid-spiked seawater. From comparison of FTIR signatures of adsorbent before and after the seawater exposure, we found that the amidoxime ligands in the adsorbent exposed to dissolved Fe-spiked seawater had severer degradation than the adsorbents exposed to humic acid-spiked seawater and unspiked clean seawater. Notably, unlike the adsorbent exposed to dissolved Fe-spiked seawater, the adsorbent exposed to humic acid-spiked seawater didn’t adsorb elevated level of Fe compared to the adsorbent in the unspiked clean seawater. This suggests that the species of Fe in the humic acid-spiked seawater (primarily humic acid bound Fe) didn’t interact with amidoxime-based adsorbent; while the Fe species in the Fe-spiked seawater strongly interacted with adsorbent and caused significant degradation of amidoxime ligands. On the other hand, highly variable uranium adsorption loadings were observed in adsorbent in contact with humic acid-spiked seawater, but not in the adsorbents exposed to dissolved Fe-spiked seawater and seawater without spike. Our observations thus indicate that seawater receiving high inputs of DOM and dissolved Fe, such as coastal waters, is not ideal for efficient extraction of uranium.
High-power ultrasonic actuators are generally assembled with a horn, backing, stress bolt, piezoelectric rings, and electrodes. The manufacturing process is complex, expensive, difficult, and time-consuming. The internal stress bolt needs to be insulated and presents a potential internal discharge point, which can decrease actuator life. Also, the introduction of a center hole for the bolt causes many failures, reducing the throughput of the manufactured actuators. A new design has been developed for producing ultrasonic horn actuators. This design consists of using flexures rather than stress bolts, allowing one to apply pre-load to the piezoelectric material. It also allows one to manufacture them from a single material/plate, rapid prototype them, or make an array in a plate or 3D structure. The actuator is easily assembled, and application of pre-stress greater than 25 MPa was demonstrated. The horn consists of external flexures that eliminate the need for the conventional stress bolt internal to the piezoelectric, and reduces the related complexity. The stress bolts are required in existing horns to provide prestress on piezoelectric stacks when driven at high power levels. In addition, the manufacturing process benefits from the amenability to produce horn structures with internal cavities. The removal of the pre-stress bolt removes a potential internal electric discharge point in the actuator. In addition, it significantly reduces the chances of mechanical failure in the piezoelectric stacks that result from the hole surface in conventional piezoelectric actuators. The novel features of this disclosure are: 1. A design that can be manufactured from a single piece of metal using EDM, precision machining, or rapid prototyping. 2. Increased electromechanical coupling of the horn actuator. 3. Higher energy density. 4. A monolithic structure of a horn that consists of an external flexure or flexures that can be used to pre-stress a solid piezoelectric structure rather than a bolt, which requires a through hole in the piezoelectric material. 5. A flexure system with low stiffness that accommodates mechanical creep with minor reduction in pre-stress.
After 6 years of planning efforts, in June 2013, Newport News Shipbuilding (NNS) began the execution phase of the inactivation of the USS Enterprise. The USS Enterprise decommissioning involves implementation of a new approach to defueling aircraft carriers, utilizing new processes for defueling and shipment of spent nuclear fuel and waste. During planning for this complex endeavor, NNS developed several process improvement initiatives including streamlining waste management processes and technology insertion using modeling and simulation (M and S) capabilities. One of the new approaches involves the establishment of a Waste Packaging Area (WPA) onboard the ship. The process assists with maximizing waste loading and shipments directly from the ship. Another waste management initiative includes the NNS/ Waste Vendor teaming effort to facilitate more efficient loading and shipment of inactivation waste. With execution underway, these initiatives are being put to the test to see if they can withstand the rigors of day-to-day production. NNS has implemented the use of the Modeling and Simulation (M and S) technology. During the planning phase, the M and S 3D Spatial Arrangement Tool was utilized to determine the optimal equipment layout within the new M-290 facility used for spent fuel packaging and ship-out and to determine the appropriate shipping container placement on the ship to maximize waste loading. The M and S technology proved to be a beneficial application resulting in continued utilization through the execution phase of the carrier inactivation. NNS is currently expanding the M-290 Facility Model to provide a visual representation of the facility, its processes, resources, and variable parameters that can be utilized as a decision support tool through simulation of the spent fuel packaging and ship-out process through the facility's life-cycle. NNS is also expanding the application of the waste management model to effectively predict waste forecast. The simulation model is linked with the defueling schedule which captures the operational elements of the waste flow process. The model extrapolates the data to provide waste generation output to assess the most efficient and cost effective path for radiological waste shipments offsite. The ability to conduct waste forecasting allows streamlining of the waste management process in support of complex defueling operations. (authors)
The structure of the non-axisymmetric heat load distribution at the divertor plates is determined not only by the toroidal but also from the poloidal spectrum of non-axisymmetric field perturbations. Whether they are intrinsic, like error fields, or they are applied through 3D coils, the non-axisymmetric fields produce complex 3D edge magnetic topologies (footprints) that alter the properties of the heat and particle flux distributions on the divertor target plates. In this manuscript, a study of the impact of applied 3D field poloidal spectrum on the footprint size and structure is done for the DIII-D tokamak using the resistive MHD code M3D-C1 coupled with the field line tracing code TRIP3D. To resolve the impact of the poloidal spectrum of the magnetic perturbation, the relative phase of the two rows of in-vessel 3D coils used to produce both a n = 2 and a n = 3 perturbation is varied, where n is the toroidal harmonic of the magnetic perturbation. This shows that the largest footprint is predicted when the relative phase of the two rows is close to zero, which is also where the resonant coupling with the plasma is maximized. These results suggest that it will be challenging to decouple the footprint size from the requisite resonant coupling for RMP–ELM control. The correlation between the measured heat load and particle flux distributions at the outer divertor plates in DIII-D and the magnetic measurements is in good agreement with the predicted dependence of the magnetic footprint size on the amplitude of the resonant component of the plasma response.
Additively manufactured lattice truss structures, often referred to as architected cellular materials, present significant advantages over conventional structures due to their unique characteristics such as high strength-to-weight ratios and surface area-to-volume ratios. These geometrically complex structures, however, come with concomitant challenges for qualification and inspection. In this study, compression testing interrupted with micro-computed tomography inspection was conducted to monitor the evolution of global and local deformation throughout the loading process of 304L stainless steel octet truss lattice structures. Both two- and three-dimensional image analysis techniques were leveraged to characterize geometric heterogeneities resulting from the laser powder bed fusion manufacturing process as well as track the structure throughout deformation. Variations from model-predicted behavior resulting from these heterogeneities are considered relative to the predicted and actual responses of the structures during compression to better understand, model, and predict the octet truss lattice structure compression response.
Plate motion near the fault gouge layer, and the elastic interplay between the gouge layer and the plate under stick-slip conditions, is key to understanding the dynamics of sheared granular fault systems. Here, a two-dimensional implementation of the combined finite-discrete element method (FDEM), which merges the finite element method (FEM) and the discrete element method (DEM), is used to explicitly simulate a sheared granular gouge fault system. In this work we focus on investigating the influence of normal load, driving shear velocity and plate stiffness on the velocities and displacements in the direction parallel to the shear direction (x-direction) measured at locations on the upper and lower plates just adjacent to the gouge. The simulations show that during slip phases the magnitudes of the measured velocities on the upper and lower plates are proportional to the normal load and may be inversely proportional to the square root of the plate's shear modulus. Whereas, the driving shear velocity does not show distinct influence on the measured velocities. Additionally, large slip velocities are generally associated with large macroscopic friction coefficient drops. For the models subjected to smaller normal loads, larger shear velocities and with stiffer shear plates, the same magnitude of slip velocity could cause a larger drop of macroscopic friction coefficient. During stick phases, the velocities of the upper and lower plates are respectively slightly greater and slightly smaller than half of the driving shear velocity and are both in the same direction of shear. The shear strain rate of the gouge is calculated from this velocity difference between the upper and lower plate during stick phases and thus the gouge effective shear modulus can be calculated. The results show that the gouge effective shear modulus increases proportionally with normal load, while the influence of shear velocity and plate stiffness on gouge effective shear modulus is minor. The simulations address the dynamics of a laboratory-scale fault gouge system and may aid in revealing the complexities of earthquake frictional dynamics.
Catalyst inks used to make fuel-cell electrodes consist of Pt/C catalyst particles and a perfluorosulfonic acid (PFSA) ionomer dispersed in water/alcohol solvent mixtures. PFSA ionomer in the ink adsorbs to the surface of the catalyst particles, dictating the dispersion colloid properties. Following adsorption, the subsequent distribution of excess nonadsorbed ionomer in the ink then governs the final structure of the electrode. Here, we characterize the adsorption of the PFSA ionomer onto Pt/C catalyst particles. PFSA adsorption is largely irreversible. Adsorbed sulfonic-acid moieties impart a negative charge on the catalyst surface, causing electrostatic repulsion between the free ionomer in solution and the ionomer-covered Pt/C particle surface. The amount of adsorption is limited by the resulting electrostatic charge that grows as more ionomer adsorbs, and the catalyst surface becomes more negatively charged. Attenuating electrostatic repulsion by increasing the ink ionic strength promotes ionomer adsorption. Electrostatically limited adsorption is observed, irrespective of the solvent water/n-propanol ratio or the catalyst particle porosity and Pt loading. Experimentally measured ionomer adsorption isotherms are well predicted by a Smoluchowski-based kinetic adsorption model, in which the electrostatic energy barrier for adsorption is predicted from DLVO theory. These findings help to unravel the complex phenomena within these colloidal dispersions, allowing for subsequent tailoring of inks to optimize fuel-cell electrode structure and performance.
A pulsed spallation target is subjected to very short (∼0.7μs) but intense loads (23.3 kJ) from repeated proton pulses, which knock away neutrons from the mercury atoms’ nuclei for a wide range application in physics, engineering, medicine, petroleum exploration, biology, chemistry, etc. The effect of this pulsed loading on the stainless-steel target module which contains the flowing mercury target material is difficult to predict not only due to its short but intense explosive-like physical reaction, but also the nonlinear material behavior of the liquid mercury in the structure. Injecting small helium bubbles in the mercury has been an efficient method of mitigating the pressure wave at high power level stage. However, prediction of the resultant loading on the target is more difficult when helium gas is intentionally injected into the mercury. A 2-phase material model that incorporates the Rayleigh-Plesset (R-P) model is expected to address this complex multi-physics dynamics problem by including the bubble dynamics in the liquid mercury. A parameter sensitivity study was firstly employed to understand their impact on the simulation strains. The investigated parameters included E, μ, γ, σ, n, VFgas, and gas cumulative volume curve control parameters a and b. Verification and validation results from sparse polynomial expansions (SPE) method and directional Gaussian smoothing (DGS) optimization show that the surrogate model had training error of ∼7% and validation error of ∼15%, indicating that machine learning methods and surrogate models can help optimize the uncertain parameters in the complex 2-phase material model. This approach is expected to fill the knowledge gap between unknown liquid-gas mixture material model and measured vessel strain responses.
Used nuclear fuel facilities need to control and minimize radioactive emissions. Off-gas systems are designed to remove radioactive contaminants, such as 85Kr, 14C, 3H, and 129I. In an off-gas system, any capture material will be exposed to a gas stream for months at a time. This gas stream may be at elevated temperature and could contain water, NOx gas, or a variety of other constituents comprising the dissolver off-gas stream in a nuclear fuel reprocessing plant. For this reason, it is important to evaluate the effects of long-term exposure, or aging, on proposed capture materials. One material under consideration is reduced silver mordenite (Ag0Z), which is recognized for its efficient iodine capture properties. Iodine is immobilized on Ag0Z as AgI, a solid with low volatility (m.p. ≥ 500°C). The aim of this study was to determine whether extended aging at elevated temperature in a nominally 2% NO2 environment would result in a loss of immobilized iodine from this material due to either physical or chemical changes that might occur during aging. Charges of iodine-loaded reduced silver mordenite (I2-Ag0Z) were exposed to a 2% NO2 environment for 1, 2, 3, and 4 months at 150°C, then analyzed for iodine losses The aging study was completed successfully. The material did not visibly change color or form. The results demonstrate that no significant iodine loss was observed over the course of 4 months of 2% NO2 aging of I2-Ag0Z at elevated temperature within the margin of error and the variability (~10%) in the loading along the beds. This provides assurance that iodine will remain immobilized on Ag0Z during extended online use in an off-gas capture treatment system. Future tests should expose I2-Ag0Z to progressively more complex feed gases in an effort to accurately replicate the conditions expected in a reprocessing facility.
The accuracy and robustness of a two-dimensional smoothing methodology is examined for the problem of recovering accurate interlaminar shear stress distributions in laminated composite and sandwich plates. The smoothing methodology is based on a variational formulation which combines discrete least-squares and penalty-constraint functionals in a single variational form. The smoothing analysis utilizes optimal strains computed at discrete locations in a finite element analysis. These discrete strain data are smoothed with a smoothing element discretization, producing superior accuracy strains and their first gradients. The approach enables the resulting smooth strain field to be practically C1-continuous throughout the domain of smoothing, exhibiting superconvergent properties of the smoothed quantity. The continuous strain gradients are also obtained directly from the solution. The recovered strain gradients are subsequently employed in the integration o equilibrium equations to obtain accurate interlaminar shear stresses. The problem is a simply-supported rectangular plate under a doubly sinusoidal load. The problem has an exact analytic solution which serves as a measure of goodness of the recovered interlaminar shear stresses. The method has the versatility of being applicable to the analysis of rather general and complex structures built of distinct components and materials, such as found in aircraft design. For these types of structures, the smoothing is achieved with 'patches', each patch covering the domain in which the smoothed quantity is physically continuous.
Since 2014, the Veggie vegetable production system on the International Space Station has intermittently supplied astronaut crews with fresh produce. To assess the potential for continuous crop production in Veggie and develop a baseline for future space crop production systems, a 120-day study was conducted to determine methodology for inputs, optimal yield, food safety standards, and crew involvement. ‘Amara’ mustard and ‘Red Russian’ kale were grown as initial crops, followed by ‘Extra Dwarf’ pakchoi and shungiku as final crops. Previous grow-outs in Veggie have included harvests at 28-35 days after initiation. In this study, a 56-day grow-out with multiple harvests from the same plants was compared to the conventional, single harvest Veggie schedule. Unlike previous Veggie studies which grew all plants simultaneously, this test staggered initiation and harvest, aiming for consistent and increased production. Plant pillows were initiated in pairs weekly and positioned to reduce shading. Completed pillows were immediately replaced with fresh ones. The multi-harvest scheme used fewer pillows, totaling 46% less pillow mass than the single harvest method. Yield varied by crop and harvest scheme, when compared as fresh edible biomass production across 56-day time increments. ‘Red Russian’ kale yielded similarly across harvest schemes. In the multiple-harvest schedule, ‘Amara’ mustard and shungiku yielded 23% to 25% higher, respectively, while ‘Extra Dwarf’ pakchoi had 43% lower yield. Microbial analysis of the plants indicated no culturable human pathogens. Microbial load of a given plant appeared to depend more on system age than plant age; across harvest methods, aerobic plate counts from final crops were higher than those of initial crops. This project also considered the complexity of crew involvement in a continuous production scenario. New crew procedures that periodically remove plant material from the Veggie root mat would be needed under continuous production to prevent potential pathogens and unpleasant odors. This study supports future space crop production scenarios and was funded by NASA’s Human Research Program.
The International Space Station’s Veggie system intermittently supplies the crew with fresh produce. To assess the potential for continuous crop production in Veggie and develop a baseline for future space crop production systems, a 120-day study was conducted to determine methodology for inputs, optimal yield, and crew involvement. ‘Amara’ mustard and ‘Red Russian’ kale were grown as initial crops, followed by ‘Extra Dwarf’ pak choi and shungiku as final crops. Previous grow-outs in Veggie have included harvests at 28-35days after initiation. In this study, a 56-day grow-out with multiple harvests from the same plants was compared to the conventional, single harvest Veggie schedule. Unlike previous Veggie studies which grew all plants simultaneously, this test staggered initiation and harvest, aiming for consistent and increased production. Plant pillows were initiated in pairs weekly and positioned to reduce shading. Completed pillows were immediately replaced with fresh ones. The multi-harvest scheme used fewer pillows, totaling 46% less pillow mass than the single harvest method. Scaled to 56-day increments, yield varied by crop and harvest scheme. ‘Red Russian’ kale yielded similarly across harvest schemes. In the multiple-harvest schedule, ‘Amara’ mustard and shungiku yielded 23% to 25% higher, respectively, while ‘Extra Dwarf’ pak choi had43% lower yield. Microbial analysis of the plants indicated no culturable human pathogens. Microbial load of a given plant appears to depend more on system age than plant age. Across harvest methods, aerobic plate counts from final crops were higher than those of initial crops. This project also considered the complexity of crew involvement in a continuous production scenario. New crew procedures that periodically remove plant material from the Veggie root mat are needed under continuous production to prevent potential pathogens and unpleasant odors. This study supports future space crop production scenarios and was funded by NASA’s Human Research Program.
Viruses and other bioagents are of high medical and biodefense concern and their detection at concentrations well below the threshold necessary to cause health hazards continues to be a challenge with respect to sensitivity, specificity, and selectivity. Ideally, assays for accurate and real time detection of viral agents and other bioagents would not necessitate any pre-processing of the analyte, which would make them applicable for example to bodily fluids (blood, sputum) and man-made as well as naturally occurring bodies of water (pools, rivers). We describe herein a robust biosensor that combines the sensitivity of surface acoustic waves (SAW) generated at a frequency of 325 MHz with the specificity provided by antibodies and other ligands for the detection of viral agents. In preferred embodiments, a lithium tantalate based SAW transducer with silicon dioxide waveguide sensor platform featuring three test and one reference delay lines was used to adsorb antibodies directed against Coxsackie virus B4 or the negative-stranded category A bioagent Sin Nombre virus (SNV), a member of the genus Hantavirus, family Bunyaviridae, negative-stranded RNA viruses. Rapid detection (within seconds) of increasing concentrations of viral particles was linear over a range of order of magnitude for both viruses, although the sensor was approximately 50.times.10.sup.4-fold more sensitive for the detection of SNV. For both pathogens, the sensor's selectivity for its target was not compromised by the presence of confounding Herpes Simplex virus type 1. The biosensor was able to detect SNV at doses lower than the load of virus typically found in a human patient suffering from hantavirus cardiopulmonary syndrome (HCPS). Further, in a proof-of-principle real world application, the SAW biosensor was capable of selectively detecting SNV agents in complex solutions, such as naturally occurring bodies of water (river, sewage effluent) without analyte pre-processing.