Performance analysis of a triple pressure hrsg

Operating characteristics of a triple pressure reheat HRSG are analyzed using a commercial software package (Gate Cycle by GE Enter Software). The calculation routine determines all the design parameters including configuration and area of each heat exchanger. The off-design calculation part has the capability of simulating the effect of any operating parameters such as power load, process requirements, and operating mode, etc., on the transient performance of the plant. The arrangement of high-temperature and intermediate-temperature components of the HRSG is changed, and its effect on the steam turbine performance and HRSG characteristics is examined. It is shown that there could be a significant difference in HRSG sizes even though thermal performance is not in great deviation. From the viewpoint of both economics and steam turbine performance, it should be carefully reviewed whether the optimum design point could exist. Off-design performance could be one of the main factors in arranging components of the HRSG because power plants operate at various off-design conditions such as ambient tempera-ture and gas turbine load, etc. It is shown that different heat exchanger configurations lead to different performances with ambient temperature, even though they have almost the same performances at design points.     

Refractive sapphire microlenses fabricated by chlorine-based inductively coupled plasma etching

We have fabricated refractive sapphire microlenses and characterized their properties for what we believe to be the first time. We use thermally reflown photoresist lenslet patterns as a mask for chlorine-based dry etch of sapphire. Pattern transfer to the mechanically hard and chemically inert sapphire substrate is made possible by an inductively coupled plasma etch system that supplies a high-density plasma gas. Processed sapphire microlenses exhibit properties close to the ideal and operate nearly in the diffraction limit.     

A vehicle routing problem solved by using a hybrid genetic algorithm

The main purpose of this study is to find out the best solution of the vehicle routing problem simultaneously considering heterogeneous vehicles, double trips, and multiple depots by using a hybrid genetic algorithm. This study suggested a mathematical programming model with a new numerical formula which presents the amount of delivery and sub-tour elimination. This model gives an optimal solution by using OPL-STUDIO(ILOG CPLEX). This study also suggests a hybrid genetic algorithm (HGA) which considers the improvement of generation for an initial solution, three different heuristic processes, and a float mutation rate for escaping from the local solution in order to find the best solution. The suggested HGA is also compared with the results of a general genetic algorithm and existing problems suggested by Eilon and Fisher. We found better solutions rather than the existing genetic algorithms.     

Use of Recombinant Bioluminescent Bacteria for On-Site Monitoring of Toluene Analogs at Petroleum Contaminated Sites

This paper describes the application of a genetically engineered microorganism, Pseudomonas putida mt-2 KG1206, to monitor toluene analogs in groundwater collected from petroleum hydrocarbon contaminated sites. KG1206 contains the intact TOL plasmid and a second plasmid with the Pm-lux gene allowing it to produce bioluminescence in the presence of toluene analogs and their derivatives such as toluene, xylenes, and m-toluate. The simple bioluminescence assay consisted of mixing one volume of groundwater sample with four volumes of broth culture followed by bioluminescence measurement after 30?min. The maximum bioluminescent response with pure chemicals followed the order: m-methyl benzyl alchohol>m-toluate>toluene>m-xylene>benzoate>p-xylene>o-xylene. The bioluminescence production was well correlated to the m-toluate concentrations (R2>0.97) in field samples, with concentrations predicted from the bioassay falling within 75–158% of true concentration. However, no strong correlation was observed between the bioluminescence intensity and the total inducer concentration in the groundwater. Results from this study demonstrate the potential of using recombinant bioluminescent bacteria as a rapid and simple tool for monitoring specific pollutants at contaminated sites.     

A 10-bit 205-MS/s 1.0- mm2 90-nm CMOS Pipeline ADC for Flat Panel Display Applications

This paper describes a 10-bit 205-MS/s pipeline analog-to-digital converter (ADC) for flat panel display applications with the techniques to alleviate the design limitations in the deep-submicron CMOS process. The switched source follower combined with a resistor-switch ladder eliminates the sampling switches and achieves high linearity for a large single-ended input signal. Multistage amplifiers adopting the complementary common-source topology increase the output swing range with lower transconductance variation and reduce the power consumption. The supply voltage for the analog blocks is provided by the low drop-out regulator for a high power-supply rejection ratio (PSRR) under the noisy operation environment. The pipeline stages of the ADC are optimized in the aspect of power consumption through the iterated calculation of the sampling capacitance and transconductance. The ADC occupies an active area of 1.0 mm² in a 90-nm CMOS process and achieves a 53-dB PSRR for a 100-MHz noise tone with the regulator and a 55.2-dB signal-to-noise-and-distortion ratio for a 30-MHz 1.0-V_PP single-ended input at 205 MS/s. The ADC core dissipates 40 mW from a 1.0-V nonregulated supply voltage.     

A 9‐Bit 80‐MS/s CMOS Pipelined Folding A/D Converter with an Offset Canceling Technique

A 9‐bit 80‐MS/s CMOS pipelined folding analog‐to‐digital converter employing offset‐canceled preamplifiers and a subranging scheme is proposed to extend the resolution of a folding architecture. A fully differential dc‐decoupled structure achieves high linearity in circuit design. The measured differential nonlinearity and integral nonlinearity of the prototype are ×0.6 LSB and ×1.6 LSB, respectively.     

Iron‐Oxide‐Based Nanovector for Tumor Targeted siRNA Delivery in an Orthotopic Hepatocellular Carcinoma Xenograft Mouse Model

Hepatocellular carcinoma (HCC) is one of the deadliest cancers worldwide. Small interfering RNA (siRNA) holds promise as a new class of therapeutics for HCC, as it can achieve sequence‐specific gene knockdown with low cytotoxicity. However, the main challenge in the clinical application of siRNA lies in the lack of effective delivery approaches that need to be highly specific and thus incur low or no systemic toxicity. Here, a nonviral nanoparticle‐based gene carrier is presented that can specifically deliver siRNA to HCC. The nanovector (NP‐siRNA‐GPC3 Ab) is made of an iron oxide core coated with chitosan‐polyethylene glycol (PEG) grafted polyethyleneimine copolymer, which is further functionalized with siRNA and conjugated with a monoclonal antibody (Ab) against human glypican‐3 (GPC3) receptor highly expressed in HCC. A rat RH7777 HCC cell line that coexpresses human GPC3 and firefly luciferase (Luc) is established to evaluate the nanovector. The nanoparticle‐mediated delivery of siRNA against Luc effectively suppresses Luc expression in vitro without notable cytotoxicity. Significantly, NP‐siLuc‐GPC3 Ab administered intravenously in an orthotopic model of HCC is able to specifically bound to tumor and induce remarkable inhibition of Luc expression. The findings demonstrate the potential of using this nanovector for targeted delivery of therapeutic siRNA to HCC.     

Classification of road surface status using a 94 GHz dual-channel polarimetric radiometer

In this article, we classify road surface statuses using a Bayesian classification method. This article uses principal component analysis (PCA) that combines a 94 GHz dual-channel polarimetric radiometer. The radiometer is used to investigate the behaviour of the brightness temperature (BT) of different road surface statuses in an open-air laboratory. The aim of this investigation is to characterize four different road surface classes (dry, wet, snowy and icy). Here, the BT (radiothermal emission) characteristics are measured at horizontal and vertical polarizations. For a given database of weather information (including BT, road surface temperature, wind speed, etc.), a PCA subspace is constructed, and the score vectors are classified by solving the Bayesian classification method. As a result, the road surface statuses were found to be well classified by the proposed method in real time.     

Estimating plot volume using lidar height and intensity distributional parameters

This study explored the feasibility of height distributional metrics and intensity values extracted from low-density airborne light detection and ranging (lidar) data to estimate plot volumes in dense Korean pine (Pinus koraiensis) plots. Multiple linear regression analyses were performed using lidar height and intensity distributional metrics. The candidate variables for predicting plot volume were evaluated using three data sets: total, canopy, and integrated lidar height and intensity metrics. All intensities of lidar returns used were corrected by the reference distance. Regression models were developed using each data set, and the first criterion used to select the best models was the corrected Akaike Information Criterion (AIC_c). The use of three data sets was statistically significant at R² = 0.75 (RMSE = 52.17 m³ ha^?1), R² = 0.84 (RMSE = 45.24 m³ ha^?1), and R² = 0.91 (RMSE = 31.48 m³ ha^?1) for total, canopy, and integrated lidar distributional metrics, respectively. Among the three data sets, the integrated lidar metrics-derived model showed the best performance for estimating plot volumes, improving errors up to 42% when compared to the other two data sets. This is attributed to supplementing variables weighted and biased to upper limits in dense plots with more statistical variables that explain the lower limits. In all data sets, intensity metrics such as skewness, kurtosis, standard deviation, minimum, and standard error were employed as explanatory variables. The use of intensity variables improved the accuracy of volume estimation in dense forests compared to prior research. Correction of the intensity values contributed up to a maximum of 58% improvement in volume estimation when compared to the use of uncorrected intensity values (R² = 0.78, R² = 0.53, and R² = 0.63 for total, canopy, and integrated lidar distributional metrics, respectively). It is clear that the correction of intensity values is an essential step for the estimation of forest volume.