Delineating groundwater-surface water exchange flux using temperature-time series analysis methods

Groundwater-surface water interactions can play a crucial role in river-, riparian and wetland management. Their delineation and quantification at various spatial and temporal scales has become an important aspect in the study of contaminant transport and attenuation processes at the groundwater-surface water interface. One of the main parameters of interest is the groundwater-surface water exchange flux, which provides indications regarding stream-aquifer connectivity, the local flow regime as well as hydrogeological properties of the streambed. One of the methods to assess vertical exchange flux is through the analysis of temperature time-series. In this paper we delineate vertical exchange flux from temperature-time series collected at a Belgian River by comparing established numerical and analytical techniques with a novel approach. Results indicate a spatial variability of vertical fluxes over two orders of magnitude at the site

A parametrized three-dimensional model for MEMS thermal shear-stress sensors

This paper presents an accurate and efficient model of MEMS thermal shear-stress sensors featuring a thin-film hotwire on a vacuum-isolated dielectric diaphragm. We consider three-dimensional (3-D) heat transfer in sensors operating in constant-temperature mode, and describe sensor response with a functional relationship between dimensionless forms of hotwire power and shear stress. This relationship is parametrized by the diaphragm aspect ratio and two additional dimensionless parameters that represent heat conduction in the hotwire and diaphragm. Closed-form correlations are obtained to represent this relationship, yielding a MEMS sensor model that is highly efficient while retaining the accuracy of three-dimensional heat transfer analysis. The model is compared with experimental data, and the agreement in the total and net hotwire power, the latter being a small second-order quantity induced by the applied shear stress, is respectively within 0.5% and 11% when uncertainties in sensor geometry and material properties are taken into account. The model is then used to elucidate thermal boundary layer characteristics for MEMS sensors, and in particular, quantitatively show that the relatively thick thermal boundary layer renders classical shear-stress sensor theory invalid for MEMS sensors operating in air. The model is also used to systematically study the effects of geometry and material properties on MEMS sensor behavior, yielding insights useful as practical design guidelines

Design and Modeling of Micromechanical GaAs based Hot Plate for Gas Sensors

For modern Gas sensors, high sensitivity and low power are expected. This paper discusses design, simulation and fabrication of new Micromachined Thermal Converters (MTCs) based on GaAs developed for Gas sensors. Metal oxide gas sensors generally work in high temperature mode that is required for chemical reactions to be performed between molecules of the specified gas and the surface of sensing material. There is a low power consumption required to obtain the operation temperatures in the range of 200 to 500 oC. High thermal isolation of these devices solves consumption problem and can be made by designing of free standing micromechanical hot plates. Mechanical stability and a fast thermal response are especially significant parameters that can not be neglected. These characteristics can be achieved with new concept of GaAs thermal converter.Comment: Submitted on behalf of EDA Publishing Association (http://irevues.inist.fr/EDA-Publishing

Accuracy of HVAC Load Predictions: Validation of EnergyPlus and DOE-2 using FLEXLAB Measurements

The aim of the project reported here was to better understand the level of accuracy of three building energy simulation (BES) engines (‘engines’) — EnergyPlus™, DOE-2.1e, and DOE-2.2 — by identifying and investigating significant deviations between the performance predicted by these engines and actual performance as measured in the FLEXLAB® test facility at Lawrence Berkeley National Laboratory (LBNL). The specific test conditions included some of those prescribed in ANSI/ASHRAE Standard 140 - Standard Method of Test for the Evaluation of Building Energy Analysis Computer Programs. Detailed measurements of FLEXLAB performance, including indoor temperatures and heat fluxes and air-flow and water flow rates and temperatures in the Heating, Ventilating and Air Conditioning (HVAC) system, together with hourly weather data, were recorded and used in analyzing the simulation results from EnergyPlus v8.8, DOE-2.2 v3.65 and DOE-2.1e v127. These engines are commonly used in the United States for building energy code compliance, federal, state, and utility incentives programs, as well as energy efficient design of new buildings and energy retrofit of existing buildings. Seven conventional overhead mixing ventilation scenarios were tested and each engine was found to have a similar level of agreement with the measurements of space-level heating and sensible cooling loads. These results provide useful information regarding the accuracy of these engines in predicting the cooling and heating load elements of whole building energy performance. This information is intended for practitioners who are concerned about transitioning between simulation tools with different engines and for managers of utility programs leveraging these tools for evaluating and/or projecting measure savings to be incentivized under their programs. The results of the comparisons of simulated and measured performance indicate that the predictions from all three engines are not significantly different. The 24-hour average value of the absolute mean bias indicates the likely magnitude of the error in any particular case. The average mean bias is reduced by cancelation of overprediction in one case by underprediction in another. The daytime absolute mean biases, which may be more important for both energy performance and occupant comfort, are ~6%, presumably because of the greater complexity involved in simulating in the presence of solar radiation. EnergyPlus typically overpredicts the cooling load and/or underpredicts the heating load by ~1.5% and the DOE-2 engines typically underpredict the cooling load by approximately the same amount. The Root Mean Square Error is relatively more sensitive to shorter term variations in the difference between predicted and measured loads; the three engines have similar values, ~10%, suggesting that the uncertainties in their predictions of peak loads may also be similar in magnitude. The implication of these results is that users, both designers and program analysts, can use EnergyPlus, DOE-2.1e, or DOE-2.2 to model conventional commercial buildings equipped with overhead mixing ventilation with a similar level of confidence. Further work is required to better understand the variability in the level of agreement between the engine predictions and FLEXLAB measurements, where a particular engine will agree well with FLEXLAB in some cases and not so well in others and another engine will agree or disagree in different cases. As the sources of this variability are identified and eliminated or reduced significantly, it is recommended that the experimental capabilities and methods developed in the study reported here should be applied to validating heating and cooling load calculations for spaces with different types of furniture and miscellaneous loads. These methods should then be applied to low energy space conditioning systems in EnergyPlus including, in particular, radiant slab and radiant ceiling panel cooling and heating systems and ‘mixed mode’ systems that combine mechanical cooling and natural ventilation systems, focusing on controls, including control of thermal mass. The work reported here addresses the conventional method of heating and cooling occupied spaces; other methods, such as the use of radiant heating and cooling systems have the potential to provide equivalent occupant comfort, or better, with lower energy consumption. These systems are addressed more explicitly in EnergyPlus but there is a need for empirical validation to give users the same level of confidence in modeling these systems that they have, or should have, in modeling conventional systems, based on the results presented here

Miniature photonic-crystal hydrophone optimized for ocean acoustics

This work reports on an optical hydrophone that is insensitive to hydrostatic pressure, yet capable of measuring acoustic pressures as low as the background noise in the ocean in a frequency range of 1 Hz to 100 kHz. The miniature hydrophone consists of a Fabry-Perot interferometer made of a photonic-crystal reflector interrogated with a single-mode fiber, and is compatible with existing fiber-optic technologies. Three sensors with different acoustic power ranges placed within a sub-wavelength sized hydrophone head allow a high dynamic range in the excess of 160 dB with a low harmonic distortion of better than -30 dB. A method for suppressing cross coupling between sensors in the same hydrophone head is also proposed. A prototype was fabricated, assembled, and tested. The sensitivity was measured from 100 Hz to 100 kHz, demonstrating a minimum detectable pressure down to 12 {\mu}Pa (1-Hz noise bandwidth), a flatband wider than 10 kHz, and very low distortion

Estimation of subsurface porosities and thermal conductivities of polygonal tundra by coupled inversion of electrical resistivity, temperature, and moisture content data

Studies indicate greenhouse gas emissions following permafrost thaw will amplify current rates of atmospheric warming, a process referred to as the permafrost carbon feedback. However, large uncertainties exist regarding the timing and magnitude of the permafrost carbon feedback, in part due to uncertainties associated with subsurface permafrost parameterization and structure. Development of robust parameter estimation methods for permafrost-rich soils is becoming urgent under accelerated warming of the Arctic. Improved parameterization of the subsurface properties in land system models would lead to improved predictions and a reduction of modeling uncertainty. In this work we set the groundwork for future parameter estimation (PE) studies by developing and evaluating a joint PE algorithm that estimates soil porosities and thermal conductivities from time series of soil temperature and moisture measurements and discrete in-time electrical resistivity measurements. The algorithm utilizes the Model-Independent Parameter Estimation and Uncertainty Analysis toolbox and coupled hydrological-thermal-geophysical modeling. We test the PE algorithm against synthetic data, providing a proof of concept for the approach. We use specified subsurface porosities and thermal conductivities and coupled models to set up a synthetic state, perturb the parameters, and then verify that our PE method is able to recover the parameters and synthetic state. To evaluate the accuracy and robustness of the approach we perform multiple tests for a perturbed set of initial starting parameter combinations. In addition, we varied types and quantities of data to better understand the optimal dataset needed to improve the PE method. The results of the PE tests suggest that using multiple types of data improve the overall robustness of the method. Our numerical experiments indicate that special care needs to be taken during the field experiment setup so that (1) the vertical distance between adjacent measurement sensors allows the signal variability in space to be resolved and (2) the longer time interval between resistivity snapshots allows signal variability in time to be resolved

Series of experiments for empirical validation of solar gain modelling in building energy simulation codes - experimental setup, test cell characterization, specifications and uncertainty analysis

Empirical validation of building energy simulation codes is an important component in understanding the capacity and limitations of the software. Within the framework of Task 34/Annex 43 of the International Energy Agency (IEA), a series of experiments was performed in an outdoor test cell. The objective of these experiments was to provide a high-quality data set for code developers and modelers to validate their solar gain models for windows with and without shading devices. A description of the necessary specifications for modeling these experiments is provided in this paper, which includes information about the test site location, experimental setup, geometrical and thermophysical cell properties including estimated uncertainties. Computed overall thermal cell properties were confirmed by conducting a steady-state experiment without solar gains. A transient experiment, also without solar gains, and corresponding simulations from four different building energy simulation codes showed that the provided specifications result in accurate thermal cell modeling. A good foundation for the following experiments with solar gains was therefore accomplished

LPMLE3 : a novel 1-D approach to study water flow in streambeds using heat as a tracer

We introduce LPMLE3, a new 1-D approach to quantify vertical water flow components at streambeds using temperature data collected in different depths. LPMLE3 solves the partial differential equation for coupled water flow and heat transport in the frequency domain. Unlike other 1-D approaches it does not assume a semi-infinite halfspace with the location of the lower boundary condition approaching infinity. Instead, it uses local upper and lower boundary conditions. As such, the streambed can be divided into finite subdomains bound at the top and bottom by a temperature-time series. Information from a third temperature sensor within each subdomain is then used for parameter estimation. LPMLE3 applies a low order local polynomial to separate periodic and transient parts (including the noise contributions) of a temperature-time series and calculates the frequency response of each subdomain to a known temperature input at the streambed top. A maximum-likelihood estimator is used to estimate the vertical component of water flow, thermal diffusivity, and their uncertainties for each streambed subdomain and provides information regarding model quality. We tested the method on synthetic temperature data generated with the numerical model STRIVE and demonstrate how the vertical flow component can be quantified for field data collected in a Belgian stream. We show that by using the results in additional analyses, nonvertical flow components could be identified and by making certain assumptions they could be quantified for each subdomain. LPMLE3 performed well on both simulated and field data and can be considered a valuable addition to the existing 1-D methods

Device modeling of superconductor transition edge sensors based on the two-fluid theory

In order to support the design and study of sophisticated large scale transition edge sensor (TES) circuits, we use basic SPICE elements to develop device models for TESs based on the superfluid-normal fluid theory. In contrast to previous studies, our device model is not limited to small signal simulation, and it relies only on device parameters that have clear physical meaning and can be easily measured. We integrate the device models in design kits based on powerful EDA tools such as CADENCE and OrCAD, and use them for versatile simulations of TES circuits. Comparing our simulation results with published experimental data, we find good agreement which suggests that device models based on the two-fluid theory can be used to predict the behavior of TES circuits reliably and hence they are valuable for assisting the design of sophisticated TES circuits.Comment: 10pages,11figures. Accepted to IEEE Trans. Appl. Supercon