Enhancing Hydrocarbon-Rich Bio-Oil Production via Catalytic Pyrolysis Fortified with Microorganism Pretreatment

A new method of pretreatment of corn straw with Phanerochaete chrysosporium combined with pyrolysis was proposed to improve the quality of bio-oil.The characterization results demonstrated that microbial pretreatment was an effective method to decrease the lignin,which can achieve a maximum removal rate of 44.19%.Due to the destruction of biomass structure,the content of alkali metal and alkaline earth metal is reduced.Meanwhile,the depolymerized biomass structure created better pyrolysis conditions to promote the pyrolysis efficiency,increase the average decomposition rate of pyrolysis and reduce the residue.In fast pyrolysis,because of the enrichment of cellulose and the removal of lignin,the contents of acids,linear carbonyls,furans,and sugars increased while the contents of phenols decreased.As for the catalytic pyrolysis,due to the hydrocarbon pool reaction and shape selection deoxidation of ZSM-5 catalyst,the total hydrocarbon and aromatics contents can significantly increase up to 34.37%and 30.59%,respectively,with 3 weeks of pretreatment.And the the low molecular content of bio-oil increased after pretreatment,which can significantly benefit the entry of primary pyrolysis steam into the catalyst pores to improve the catalytic efficiency and hydrocarbon contents.This method provides a new treatment idea for high-quality utilization of biomass.

RBMDO Using Gaussian Mixture Model-Based Second-Order Mean-Value Saddlepoint Approximation

Actual engineering systems will be inevitably affected by uncertain factors.Thus,the Reliability-Based Multidisciplinary Design Optimization(RBMDO)has become a hotspot for recent research and application in complex engineering system design.The Second-Order/First-Order Mean-Value Saddlepoint Approximate(SOMVSA/-FOMVSA)are two popular reliability analysis strategies that are widely used in RBMDO.However,the SOMVSA method can only be used efficiently when the distribution of input variables is Gaussian distribution,which significantly limits its application.In this study,the Gaussian Mixture Model-based Second-Order Mean-Value Saddlepoint Approximation(GMM-SOMVSA)is introduced to tackle above problem.It is integrated with the Collaborative Optimization(CO)method to solve RBMDO problems.Furthermore,the formula and procedure of RBMDO using GMM-SOMVSA-Based CO(GMM-SOMVSA-CO)are proposed.Finally,an engineering example is given to show the application of the GMM-SOMVSA-CO method.

Uncertainty-based Multidisciplinary Design Optimization using An Approximated Second-Order Reliability Analysis Strategy

In uncertainty-based multidisciplinary design optimization(UBMDO),all reliability limitation factors are maintained due to minimize the cost target function.There are many reliability evaluation methods for reliability limitation factors.The second-order reliability method(SORM)is a powerful most possible point(MPP)-based method.It can provide an accurate estimation of the failure probability of a highly nonlinear limit state function despite its large curvature.But the Hessian calculation is necessary in SORM,which results in a heavy computational cost.Recently,an efficient approximated second-order reliability method(ASORM)is proposed.The ASORM uses a quasi-Newton method to close to Hessian without the direct calculation of Hessian.To further improve the UBMDO efficiency,we also introduce the performance measure approach(PMA)and the sequential optimization and reliability assessment(SORA)strategy.To solve the optimization design problem of a turbine blade,the formula of MDO with ASORM under the SORA framework(MDO-ASORM-SORA)is proposed.

Quartz-enhanced multiheterodyne resonant photoacoustic spectroscopy

The extension of dual-comb spectroscopy(DCS)to all wavelengths of light along with its ability to provide ultralarge dynamic range and ultra-high spectral resolution,renders it extremely useful for a diverse array of applications in physics,chemistry,atmospheric science,space science,as well as medical applications.In this work,we report on an innovative technique of quartz-enhanced multiheterodyne resonant photoacoustic spectroscopy(QEMR-PAS),in which the beat frequency response from a dual comb is frequency down-converted into the audio frequency domain.In this way,gas molecules act as an optical-acoustic converter through the photoacoustic effect,generating heterodyne sound waves.Unlike conventional DCS,where the light wave is detected by a wavelengthdependent photoreceiver,QEMR-PAS employs a quartz tuning fork(QTF)as a high-Q sound transducer and works in conjunction with a phase-sensitive detector to extract the resonant sound component from the multiple heterodyne acoustic tones,resulting in a straightforward and low-cost hardware configuration.This novel QEMRPAS technique enables wavelength-independent DCS detection for gas sensing,providing an unprecedented dynamic range of 63 dB,a remarkable spectral resolution of 43 MHz(or~0.3 pm),and a prominent noise equivalent absorption of 5.99×10^(-6)cm^(-1)·Hz-1/2.