Performance Assessment and Comparison of Two Piezoelectric Energy Harvesters Developed for Pavement Application: Case Study

To advance the development of piezoelectric energy harvesters, this study designed and manufactured bridge-unit-based and pile-unit-based piezoelectric devices. An indoor material testing system and accelerated pavement test equipment were used to test the electrical performance, mechanical performance, and electromechanical coupling performance of the devices. The results showed that the elastic modulus of the pile structure device was relatively higher than that of the bridge structure device. However, the elastic modulus of the two devices should be improved to avoid attenuation in the service performance and fatigue life caused by the stiffness difference. Furthermore, the electromechanical conversion coefficients of the two devices were smaller than 10% and insensitive to the load magnitude and load frequency. Moreover, the two devices can harvest 3.4 mW and 2.6 mW under the wheel load simulated by the one-third scale model mobile load simulator, thus meeting the supply requirements of low-power sensors. The elastic modulus, electromechanical conversion coefficients, and electric performance of the pile structure device were more reliable than those of the bridge structure device, indicating a better application prospect in road engineering.

Structures of processors for calculating the instant Walsh spectrum

The work is devoted to the development of circuits for fast Walsh transform processors of the serialparallel type. The fast Walsh transform processors are designed for decoding error-correcting codes and synchronization; their use can reduce the cost of calculating the instantaneous Walsh spectrum by almost 2 times. The class of processors for computing the instantaneous spectrum according to Walsh is called serialparallel processors. Circuits of the fast Walsh transform processors of serial-parallel type have been developed. A comparative analysis of the constructed graphs of the fast Walsh transform processors is carried out. A method and a processor for calculating the Walsh transform coefficients are proposed, which allows increasing the speed of the transformations performed. When calculating the conversion coefficients using processors of parallel, serial and serial-parallel types, it was found that controllers of the serial-parallel type require 2(N–1) operations when calculating the instantaneous spectrum according to Walsh. The results obtained can be used in the design of discrete information processing devices, in telecommunication systems when coding signals for their noise-immune transmission and decoding, which ensures the optimal number of operations, and therefore the optimal hardware costs.

Skin dose contamination conversion coefficients. Benchmark with three simulation codes

Handling of radioactive material by operators can lead to contamination at the surface of the skin in case of an accident. The quantification of the dose received by the skin due to a contamination scenario is performed by means of dedicated dose coefficients as it is the case for other radiation protection dose quantities described in the literature. However, most available coefficients do not match realistic scenarios according to state-of-the-art of science and technology. Therefore, this work deals with dedicated dose conversion factors for skin contamination. Since there is an increasing demand on dose coefficients in general, these specific coefficients can be used for various calculations in radiation protection. In this work a method to evaluate such coefficients for the skin contamination dose related to photons, electrons, positrons, alpha and neutron particles is proposed. The coefficients are generated using Monte-Carlo simulations with three well established calculation codes (FLUKA, MCNP, and GEANT4). The results of the various codes are compared against each other for benchmarking purposes. The new dose coefficients allow the computation of the skin received dose, in the case of skin contamination scenario of an individual, taking into account the decay radiation of the radionuclides of interest. To benchmark the quantity derived here, comparisons of radionuclide contamination doses to the skin using the VARSKIN code available in the literature are performed with the results of this work.

Emissions of CH4 and CO2 from Wastewater of Palm Oil Mills: A Real Contribution to Increase the Greenhouse Gas and Its Potential as Renewable Energy Sources

Palm oil mill effluent (POME) treatment in Indonesia is still predominant using an open pond system. This system has the weakness of the unknown and uncontrollable value of greenhouse gas (GHG) emissions into the atmosphere. This study estimated GHG emissions (CH4 and CO2) from anaerobic ponds and their potential as a renewable energy source and obtain GHG emission conversion coefficients for each kg of COD POME and ton of crude palm oil (CPO). Gas samples were collected using a closed static chamber. GHG sample concentration testing was done using Gas Chromatography with a flame ionization detector (FID) and thermal conductivity detector (TCD). The results showed that the emission rate of CH4 and CO2 in the anaerobic pond POME treatment was relatively high, 261.93 and 595.99 g/m2/day, respectively, equivalent to 48.572 t CO2-eq/day or 14,571.5 t CO2-eq/year. CO2 emissions were greater than two times CH4 emissions, both spatially and temporally. There was a process of facultative biodegradation, aerobic and or anaerobic process according to the biotic-abiotic environment and the levels of organic components in the substrate. In anaerobic ponds, the optimal requirements for the biodegradation process tended to be unfulfilled, so the emission rate of CH4 was less than CO2. The GHG conversion coefficient was obtained, namely each kg of COD from POME emitted 6.266 kg CO2-eq of GHG; for each m3 of POME emitted by 0.163 t CO2-eq of GHG; and 0.556 t CO2-eq/t CPO. The maximum potential for POME to energy conversion was 1.045 MWe with a power capacity of 8,603 MWh/year.