Heat Pump-Based Novel Energy System for High-Power LED Lamp Cooling and Waste Heat Recovery

Unlike incandescent light bulb, which radiates heat into the surroundings by infrared rays, light emitting diode (LED) traps heat inside the lamp. This fact increases the difficulty of cooling LED lamps, while it facilitates the recovery of the generated heat. We propose a novel energy system that merges high-power LED lamp cooling with the heat pump use; the heat pump can cool the LED lamp and at the same time recover the waste heat. In this way, a high percentage of the energy consumed by the LED lamp can be utilized. In this work, we developed a prototype of this energy system and conducted a series of experimental studies to determine the effect of several parameters, such as cooling water flow rate and LED power, on the LED leadframe temperature, compressor power consumption, and system performance. The experimental results clearly indicate that the energy system can lead to substantial energy savings

A novel three-dimensional transient model for subsurface heat exchange in enhanced geothermal systems

Understanding the subsurface heat exchange process in enhanced geothermal systems (EGS) is crucial to the efficiency of heat extraction and the sustainable utilization of geothermal reservoir. In the present work we develop a novel three-dimensional transient model for the study of the subsurface heat exchange process in EGS. The novelty of this model is embodied by a couple of salient features. First, the geometry of interest physically consists of multiple domains: open channels for injection and production wells, the artificial heat reservoir, and the rock enclosing the heat reservoir, while computationally we treat it as a single-domain of multiple sub-regions associated with different sets of characteristic properties (porosity and permeability etc.). This circumvents typical difficulties about matching boundary conditions between sub-domains in traditional multi-domain approaches and facilitates numerical implementation and simulation of the complete subsurface heat exchange process. Second, the heat reservoir is treated as an equivalent porous medium of a single porosity, while we consider thermal non-equilibrium between solid and fluid components and introduce two sets of heat transfer equations to describe the heat advection and conduction for fluid in rock apertures and the heat conduction in rock matrix, respectively, thus enabling the simulation and analysis of convective heat exchange between rock matrix and fluid flowing in the apertures. Case study with respect to an imaginary EGS demonstrates the validity and capability of the developed model. (C) 2012 Elsevier Ltd. All rights reserved

A three-dimensional transient model for EGS subsurface thermo-hydraulic process

Understanding the subsurface thermo-hydraulic process in enhanced or engineered geothermal systems (EGS) is crucial to the efficiency of heat extraction and the sustainable utilization of geothermal reservoir. We present in detail a three-dimensional transient model for the study of subsurface thermo-hydraulic process during EGS heat extraction and demonstrate its capability through test simulations. Since this model considers the actual existence of local thermal non-equilibrium between rock matrix and fluid flowing in the porous heat reservoir during EGS heat extraction, the model results shed light on the local heat exchange in the reservoir. One other salient feature of this model is its capability of simulating the complete subsurface thermo-hydraulic process during EGS heat extraction, not only the thermo-flow in the reservoir and well boreholes, but also the heat conduction or transport in rocks enclosing the reservoir. The results obtained from the test simulations, though the considered reservoir is imaginary and homogeneously fractured, corroborate the capability and validity of the present model. Moreover, the model results from the specially designed triplet well EGS case indicate its superior heat extraction performance. (C) 2014 Elsevier Ltd. All rights reserved

GNSS Signal Compression Acquisition Algorithm Based on Sensing Matrix Optimization

Due to the sparsity of GNSS signal in the correlation domain, compressed sensing theory is considered to be a promising technology for GNSS signal acquisition. However, the detection probability of the traditional compression acquisition algorithm is low under low signal-to-noise ratio (SNR) conditions. This paper proposes a GNSS compression acquisition algorithm based on sensing matrix optimization. The Frobenius norm of the difference between Gram matrix and an approximate equiangular tight frame (ETF) matrix is taken as the objective function, and the modified conjugate gradient method is adopted to reduce the mutual coherence between the measurement matrix and the sparse basis. Theoretical analysis and simulation results show that the proposed algorithm can significantly improve the detection probability compared with the existing compression acquisition algorithms under the same SNR

Novel Concrete Temperature Monitoring Method Based on an Embedded Passive RFID Sensor Tag

This paper firstly introduces the importance of temperature control in concrete measurement, then a passive radio frequency identification (RFID) sensor tag embedded for concrete temperature monitoring is presented. In order to reduce the influences of concrete electromagnetic parameters during the drying process, a T-type antenna is proposed to measure the concrete temperature at the required depth. The proposed RFID sensor tag is based on the EPC generation-2 ultra-high frequency (UHF) communication protocol and operates in passive mode. The temperature sensor can convert the sensor signals to corresponding digital signals without an external reference clock due to the adoption of phase-locked loop (PLL)-based architecture. Laboratory experimentation and on-site testing demonstrate that our sensor tag embedded in concrete can provide reliable communication performance in passive mode. The maximum communicating distance between reader and tag is 7 m at the operating frequency of 915 MHz and the tested results show high consistency with the results tested by a thermocouple

Parametric Study on Thermo-Hydraulic Performance of NACA Airfoil Fin PCHEs Channels

In this work, a discontinuous airfoil fin printed circuit heat exchanger (PCHE) was used as a recuperator in a micro gas turbine system. The effects of the airfoil fin geometry parameters (arc height, maximum arc height position, and airfoil thickness) and the airfoil fin arrangements (horizontal and vertical spacings) on the PCHE channel’s thermo-hydraulic performance were extensively examined by a numerical parametric study. The flow features, local heat transfer coefficient, and wall shear stress were examined in detail to obtain an enhanced heat transfer mechanism for a better PCHE design. The results show that the heat transfer and flow resistance were mainly increased at the airfoil leading edge owing to a flow jet, whereas the airfoil trailing edge had little effect on the thermo-hydraulic performance. The airfoil thickness was the most significant while the arc height and the vertical spacing were moderately significant to the performance. Moreover, only the airfoil thickness had a significant effect on the PCHE compactness. Based on a comprehensive investigation, two solutions NACA-6230 and -3220 were selected owing to their better thermal performance and smaller pressure drop, respectively, with horizontal spacings of 2 mm and vertical spacings of 2 or 3 mm

New Copper Bromide Organic-Inorganic Hybrid Molecular Compounds with Anionic Inorganic Core and Cationic Organic Ligands

Here, organic-inorganic hybrid molecular compounds based on copper(I) bromide have been synthesized by slow-diffusion method. The inorganic modules of these two structures are Cu2Br42− anion, and the inorganic modules are coordinated to cationic organic ligands via Cu-N coordinative bonds. Both of these compounds are luminescent, emitting green emissions under UV excitation

Nanotechnology shaping stem cell therapy: Recent advances, application, challenges, and future outlook

Currently, stem cell nanotechnology is one of the novel and exciting fields. Certain experimental studies conducted on the interaction of stem cells with nanostructures or nanomaterials have made significant progress. The significance of nanostructures, nanotechnology, and nanomaterials in the development of stem cell-based therapies for degenerative diseases and injuries has been well established. Specifically, the structure and properties of nanomaterials affecting the propagation and differentiation of stem cells have become a new interdisciplinary frontier in material science and regeneration medicines. In the current review, we highlight the recent major progress in this field, explore the application prospects, and discuss the issues, approaches, and challenges, to improve the applications of nanotechnology in the research and development of stem cells

Land Use and Land Cover Mapping Using RapidEye Imagery Based on a Novel Band Attention Deep Learning Method in the Three Gorges Reservoir Area

Land use/land cover (LULC) change has been recognized as one of the most important indicators to study ecological and environmental changes. Remote sensing provides an effective way to map and monitor LULC change in real time and for large areas. However, with the increasing spatial resolution of remote sensing imagery, traditional classification approaches cannot fully represent the spectral and spatial information from objects and thus have limitations in classification results, such as the “salt and pepper” effect. Nowadays, the deep semantic segmentation methods have shown great potential to solve this challenge. In this study, we developed an adaptive band attention (BA) deep learning model based on U-Net to classify the LULC in the Three Gorges Reservoir Area (TGRA) combining RapidEye imagery and topographic information. The BA module adaptively weighted input bands in convolution layers to address the different importance of the bands. By comparing the performance of our model with two typical traditional pixel-based methods including classification and regression tree (CART) and random forest (RF), we found a higher overall accuracy (OA) and a higher Intersection over Union (IoU) for all classification categories using our model. The OA and mean IoU of our model were 0.77 and 0.60, respectively, with the BA module and were 0.75 and 0.58, respectively, without the BA module. The OA and mean IoU of CART and RF were both below 0.51 and 0.30, respectively, although RF slightly outperformed CART. Our model also showed a reasonable classification accuracy in independent areas well outside the training area, which indicates the strong model generalizability in the spatial domain. This study demonstrates the novelty of our proposed model for large-scale LULC mapping using high-resolution remote sensing data, which well overcomes the limitations of traditional classification approaches and suggests the consideration of band weighting in convolution layers