The development of some computational algorithms based on cellular automaton was described to simulate the structures formed during the solidification of steel products.The algorithms described take results from the s...The development of some computational algorithms based on cellular automaton was described to simulate the structures formed during the solidification of steel products.The algorithms described take results from the steel thermal behavior and heat removal previously calculated using a simulator developed by present authors in a previous work.Stored time is used for displaying the steel transition from liquid to mushy and solid.And it is also used to command computational subroutines that reproduce nucleation and grain growth.These routines are logically programmed using the programming language C＋＋ and are based on a simultaneous solution of numerical methods （stochastic and deterministic） to create a graphical representation of different grain structures formed.The grain structure obtained is displayed on the computer screen using a graphical user interface （GUI）.The chaos theory and random generation numbers are included in the algorithms to simulate the heterogeneity of grain sizes and morphologies.展开更多
An algorithm for grain reconstruction based on electron backscatter diffraction data was proposed in this paper. This algorithm can well record the original data arrangement when an external file for the reconstructed...An algorithm for grain reconstruction based on electron backscatter diffraction data was proposed in this paper. This algorithm can well record the original data arrangement when an external file for the reconstructed grain（s） was exported for further post-processing. Assisted by an in-house MATLAB program, grain reconstruction, lattice rotations, orientation spreads, and slip system analysis can be performed. The validity of this algorithm has been successfully tested by polycrystalline Ni before and after channel die compression.展开更多
Computational models are developed to create grain structures using mathematical algorithms based on the chaos theory such as cellular automaton, geometrical models, fractals, and stochastic methods. Because of the ch...Computational models are developed to create grain structures using mathematical algorithms based on the chaos theory such as cellular automaton, geometrical models, fractals, and stochastic methods. Because of the chaotic nature of grain structures, some of the most popular routines are based on the Monte Carlo method, statistical distributions, and random walk methods, which can be easily programmed and included in nested loops. Nevertheless, grain structures are not well defined as the results of computational errors and numerical incon- sistencies on mathematical methods. Due to the finite definition of numbers or the numerical restrictions during the simulation of solidifica- tion, damaged images appear on the screen. These images must be repaired to obtain a good measurement of grain geometrical properties. Some mathematical algorithms were developed to repair, measure, and characterize grain structures obtained from cellular automata in the present work. An appropriate measurement of grain size and the corrected identification of interfaces and length are very important topics in materials science because they are the representation and validation of mathematical models with real samples. As a result, the developed al- gorithms are tested and proved to be appropriate and efficient to eliminate the errors and characterize the grain structures.展开更多
Optimization Algorithm was developed for the simula ti on of ceramic grain growth at atomistic scale. Based on the coordination informa tion of different atoms, a structure of trident tree was applied to save large q ...Optimization Algorithm was developed for the simula ti on of ceramic grain growth at atomistic scale. Based on the coordination informa tion of different atoms, a structure of trident tree was applied to save large q uantities data, so as to solve the problems of large data information and long r unning time. For every atom a binary tree was firstly formed according to the X coordination of atom. If the values of X coordination were the same, the middle sub-tree of first layer formed then a binary tree according to the Y coordinati on of atom. If the values of Y coordination were also the same, the middle sub- tree of second layer formed then a binary tree according to the Z coordination o f atom. In this way the speed of whole program is enhanced obviously. In order t o reduce memory, in this structure only need to store the exterior atoms’ infor mation, an integer is used to store the interior atoms’ information. If other a toms take up an atom’s all adjacent positions, this atom will be deleted in the data structure, for all the adjacent positions’ atoms, the integer’s relative bit will be set 1 to denote that there is an atom in this position but not be s tored in the trident tree. When an outside atom is deleted, for all the bits tha t are set 1,an atom will be added to the trident tree as an outside atom for the relative positions. And for this new added atom, the integer’s relative bi t of all the adjacent position’s atoms should be set 0 to denote that there is no interior atom in this position. In this way, if there are n 3 atoms, onl y need to store 6n 2 quantity’s atoms’ information. Large quantity of mem ory space can then be saved.展开更多
AISI 304L is an austenitic Chromium-Nickel stainless steel offering the optimum combination of corrosion resistance, strength and ductility. These attributes make it a favorite for many mechanical components. The pape...AISI 304L is an austenitic Chromium-Nickel stainless steel offering the optimum combination of corrosion resistance, strength and ductility. These attributes make it a favorite for many mechanical components. The paper focuses on developing mathematical models to predict grain size and hardness of pulsed current micro plasma arc welded AISI 304L joints. Four factors, five level, central composite rotatable design matrix is used to optimize the number of experiments. The mathematical models have been developed by Response Surface Method (RSM) and its adequacy is checked by Analysis of Variance (ANOVA) technique. By using the developed mathematical models, grain size and hardness of the weld joints can be predicted with 99% confidence level. The developed mathematical models have been optimized using Hooke and Jeeves algorithm to minimize grain size and maximize the hardness.展开更多
This article proposes a multidisciplinary design and optimization （MDO） strategy for the conceptual design of a multistage ground-based interceptor （GBI） using hybrid optimization algorithm, which associates genet...This article proposes a multidisciplinary design and optimization （MDO） strategy for the conceptual design of a multistage ground-based interceptor （GBI） using hybrid optimization algorithm, which associates genetic algorithm （GA） as a global optimizer with sequential quadratic programming （SQP） as a local optimizer. The interceptor is comprised of a three-stage solid propulsion system for an exoatmospheric boost phase intercept （BPI）. The interceptor＇s duty is to deliver a kinetic kill vehicle （KKV） to the optimal position in space to accomplish the mission of intercept. The modules for propulsion, aerodynamics, mass properties and flight dynamics are integrated to produce a high fidelity model of the entire vehicle. The propulsion module com- prises of solid rocket motor （SRM） grain design, nozzle geometry design and performance prediction analysis. Internal ballistics and performance prediction parameters are calculated by using lumped parameter method. The design objective is to minimize the gross lift off mass （GLOM） of the interceptor under the mission constraints and performance objectives. The proposed design and optimization methodology provide designers with an efficient and powerful approach in computation during designing interceptor systems.展开更多
Once the disaster occurred, a huge amount of grain supply is needed from disaster area. Because of the short shelf life, grain is very strict with reserve environment and needed to rotate on a regular basis in the pro...Once the disaster occurred, a huge amount of grain supply is needed from disaster area. Because of the short shelf life, grain is very strict with reserve environment and needed to rotate on a regular basis in the process of reserves. Considering the limitations of existing related research, this paper presented a facility location model for grain emergency network that incorporates inventory factors and rotation mechanism, and then designed genetic algorithm based on Matlab to solve the model. Finally we verified the feasibility and effectiveness of the algorithm by computational examples and presented the directions for future work.展开更多
In this paper, the significance and history of studying snow grain size is introduced. Based on the assumption that high reflectivity in the visible band and significant decreasing reflectivity of snow surface in the ...In this paper, the significance and history of studying snow grain size is introduced. Based on the assumption that high reflectivity in the visible band and significant decreasing reflectivity of snow surface in the infrared band, the grain size of snow, spherical and non-spherical, is sensitive to changes in remote sensing retrieval foundation. Also, models and algorithms applied in current studies are reviewed, together with their advantages and disadvantages. In addition, in order to obtain retrieval accuracy, some factors that may affect grain size are also discussed, such as temperature, wavelength, arid particle shape, as well as method authentication.展开更多
A description of a mathematical algorithm for simulating grain structures with straight and hyperbolic interfaces is shown. The presence of straight and hyperbolic interfaces in many grain structures of metallic mater...A description of a mathematical algorithm for simulating grain structures with straight and hyperbolic interfaces is shown. The presence of straight and hyperbolic interfaces in many grain structures of metallic materials is due to different solidification conditions, in- eluding different solidification speeds, growth directions, and delaying on the nucleation times of each nucleated node. Grain growth is a complex problem to be simulated; therefore, computational methods based on the chaos theory have been developed for this purpose. Straight and hyperbolic interfaces are between columnar and equiaxed grain structures or in transition zones. The algorithm developed in this work involves random distributions of temperature to assign preferential probabilities to each node of the simulated sample for nucleation according to previously defined boundary conditions. Moreover, more than one single nucleation process can be established in order to gen- erate hyperbolic interfaces between the grains. The appearance of new nucleated nodes is declared in sequences with a particular number of nucleated nodes and a number of steps for execution. This input information influences directly on the final grain structure （grain size and dislribution）. Preferential growth directions are also established to obtain equiaxed and columnar grains. The simulation is done using rou- tines for nucleation and growth nested inside the main function. Here, random numbers are generated to place the coordinates of each new nucleated node at each nucleation sequence according to a solidification probability. Nucleation and growth routines are executed as a func- tion of nodal availability in order to know if a node will be part of a grain. Finally, this information is saved in a two-dimensional computa- tional array and displayed on the computer screen placing color pixels on the corresponding position forming an image as is done in cellular automaton.展开更多
For the great significance of the prediction of control parameters selected for hot-rolling and the evaluation of hot-rolling quality for the analysis of prod uction problems and production management, the selection o...For the great significance of the prediction of control parameters selected for hot-rolling and the evaluation of hot-rolling quality for the analysis of prod uction problems and production management, the selection of hot-rolling control parameters was studied for microalloy steel by following the neural network principle. An experimental scheme was first worked out for acquisition of sample data, in which a gleeble-1500 thermal simolator was used to obtain rolling temperature, strain, stain rate, and stress-strain curves. And consequently the aust enite grain sizes was obtained through microscopic observation. The experimental data was then processed through regression. By using the training network of BP algorithm, the mapping relationship between the hotrooling control parameters (rolling temperature, stain, and strain rate) and the microstructural paramete rs (austenite grain in size and flow stress) of microalloy steel was function appro ached for the establishment of a neural network-based model of the austeuite grain size and flow stress of microalloy steel. From the results of estimation made with the neural network based model, the hot-rolling control parameters can be effectively predicted.展开更多
玉米育种过程中,灌浆期籽粒含水率检测时,通常需要脱粒,采集穗中间200粒为检测样本。为了保护亲本,避免破坏性检测,该研究提出一种基于近红外光谱的灌浆期玉米籽粒水分定量分析通用模型,用于灌浆期玉米籽粒水分的田间原位检测。首先构建...玉米育种过程中,灌浆期籽粒含水率检测时,通常需要脱粒,采集穗中间200粒为检测样本。为了保护亲本,避免破坏性检测,该研究提出一种基于近红外光谱的灌浆期玉米籽粒水分定量分析通用模型,用于灌浆期玉米籽粒水分的田间原位检测。首先构建GA-IRIV-DS光谱数据处理策略。利用遗传算法(genetic algorithm,GA)和迭代保留信息变量(iterative retention of information variables,IRIV)二次波长筛选方法,提取光谱数据中有效的水分变量信息,减小特征空间维度的同时提高模型预测精度;再结合直接校正算法(direct standardization,DS),降低预测样本与建模样本的差异性,将玉米灌浆期穗尖部籽粒光谱数据校正为中间200籽粒的光谱,使水分定量分析模型能够具备中间200籽粒和穗尖部籽粒2种检测样本的通用性。在GA-IRIV-DS光谱数据处理策略的基础上,构建基于偏最小二乘法(partial lpeast squares regression,PLSR)的水分定量分析通用模型。经过验证,GA-IRIV-DS光谱数据处理策略校正后的光谱差异性降低了59.4%。为了进一步验证GA-IRIV-DS光谱数据处理策略的有效性,分析了GA+IRIVN组合波长筛选提取光谱特征,并分别与全光谱、多种典型波长筛选方法结合DS方法构建基于偏最小二乘法(PLSR)的水分定量分析模型结果相比较。试验结果表明,两种样本预测集GA-IRIVN-DS-PLSR模型效果均优于全光谱和其他模型,中间籽粒样本和穗尖部籽粒样本的预测决定系数(R^(2))达到了0.9715和0.9012,均方根误差(RMSEP)较全光谱下降了80.10%和64.60%。证明基于GA-IRIVN-DS光谱数据处理策略建立的近红外光谱水分定量分析模型具有一定泛化能力,可以为玉米育种过程中,减少检测过程中的样本破坏和提高检测效率提供可行的参考方法。展开更多
基于近红外偏最小二乘法(near-infrared partial least squares,NIR-PLS)开发了一种近红外光谱快速检测模型,用于快速、无损检测清蒸高粱糊化度。同时分析了白酒酿造生产关键指标相关性,以清蒸高粱糊化度为基础,结合清蒸高粱感官评价、...基于近红外偏最小二乘法(near-infrared partial least squares,NIR-PLS)开发了一种近红外光谱快速检测模型,用于快速、无损检测清蒸高粱糊化度。同时分析了白酒酿造生产关键指标相关性,以清蒸高粱糊化度为基础,结合清蒸高粱感官评价、出入窖糟醅理化、出酒率、基础酒理化及评分,利用自适应权重算法(adaptive weights,AW)建立了一种清蒸高粱蒸粮效果评价方法。该检测模型在预测清蒸高粱糊化度方面具有较高的相关性,模型预测值与建模参考值之间的决定系数R^(2)=0.9771。此外,蒸粮效果评价方法验证结果与经验丰富的酿酒师的感官评定相吻合。当75≤糊化度检测值≤80时,清蒸高粱糊化效果评价为优级;65≤糊化度检测值<75时,评价为一级;55<糊化度检测值<65或80<糊化度检测值<90时,评价为二级;糊化度检测值≥90或糊化度检测值≤55时,评价为不合格。该评价方法量化了白酒生产中清蒸高粱蒸粮效果的评定,将依赖经验的感官评估方式转化为标准化、数字化的手段,有助于加强生产过程和产品质量的可控性,减少粮食损耗。展开更多
文摘The development of some computational algorithms based on cellular automaton was described to simulate the structures formed during the solidification of steel products.The algorithms described take results from the steel thermal behavior and heat removal previously calculated using a simulator developed by present authors in a previous work.Stored time is used for displaying the steel transition from liquid to mushy and solid.And it is also used to command computational subroutines that reproduce nucleation and grain growth.These routines are logically programmed using the programming language C＋＋ and are based on a simultaneous solution of numerical methods （stochastic and deterministic） to create a graphical representation of different grain structures formed.The grain structure obtained is displayed on the computer screen using a graphical user interface （GUI）.The chaos theory and random generation numbers are included in the algorithms to simulate the heterogeneity of grain sizes and morphologies.
基金the financial support of the Ministry of Science and Technology of China (Grant No. 2012CB932201)the National Natural Science Foundation of China (Grant Nos. 51231006 and 51171182)the Danish-Chinese Center for Nanometals (Grant Nos. 51261130091 and DNRF86-5)
文摘An algorithm for grain reconstruction based on electron backscatter diffraction data was proposed in this paper. This algorithm can well record the original data arrangement when an external file for the reconstructed grain（s） was exported for further post-processing. Assisted by an in-house MATLAB program, grain reconstruction, lattice rotations, orientation spreads, and slip system analysis can be performed. The validity of this algorithm has been successfully tested by polycrystalline Ni before and after channel die compression.
文摘Computational models are developed to create grain structures using mathematical algorithms based on the chaos theory such as cellular automaton, geometrical models, fractals, and stochastic methods. Because of the chaotic nature of grain structures, some of the most popular routines are based on the Monte Carlo method, statistical distributions, and random walk methods, which can be easily programmed and included in nested loops. Nevertheless, grain structures are not well defined as the results of computational errors and numerical incon- sistencies on mathematical methods. Due to the finite definition of numbers or the numerical restrictions during the simulation of solidifica- tion, damaged images appear on the screen. These images must be repaired to obtain a good measurement of grain geometrical properties. Some mathematical algorithms were developed to repair, measure, and characterize grain structures obtained from cellular automata in the present work. An appropriate measurement of grain size and the corrected identification of interfaces and length are very important topics in materials science because they are the representation and validation of mathematical models with real samples. As a result, the developed al- gorithms are tested and proved to be appropriate and efficient to eliminate the errors and characterize the grain structures.
文摘Optimization Algorithm was developed for the simula ti on of ceramic grain growth at atomistic scale. Based on the coordination informa tion of different atoms, a structure of trident tree was applied to save large q uantities data, so as to solve the problems of large data information and long r unning time. For every atom a binary tree was firstly formed according to the X coordination of atom. If the values of X coordination were the same, the middle sub-tree of first layer formed then a binary tree according to the Y coordinati on of atom. If the values of Y coordination were also the same, the middle sub- tree of second layer formed then a binary tree according to the Z coordination o f atom. In this way the speed of whole program is enhanced obviously. In order t o reduce memory, in this structure only need to store the exterior atoms’ infor mation, an integer is used to store the interior atoms’ information. If other a toms take up an atom’s all adjacent positions, this atom will be deleted in the data structure, for all the adjacent positions’ atoms, the integer’s relative bit will be set 1 to denote that there is an atom in this position but not be s tored in the trident tree. When an outside atom is deleted, for all the bits tha t are set 1,an atom will be added to the trident tree as an outside atom for the relative positions. And for this new added atom, the integer’s relative bi t of all the adjacent position’s atoms should be set 0 to denote that there is no interior atom in this position. In this way, if there are n 3 atoms, onl y need to store 6n 2 quantity’s atoms’ information. Large quantity of mem ory space can then be saved.
文摘AISI 304L is an austenitic Chromium-Nickel stainless steel offering the optimum combination of corrosion resistance, strength and ductility. These attributes make it a favorite for many mechanical components. The paper focuses on developing mathematical models to predict grain size and hardness of pulsed current micro plasma arc welded AISI 304L joints. Four factors, five level, central composite rotatable design matrix is used to optimize the number of experiments. The mathematical models have been developed by Response Surface Method (RSM) and its adequacy is checked by Analysis of Variance (ANOVA) technique. By using the developed mathematical models, grain size and hardness of the weld joints can be predicted with 99% confidence level. The developed mathematical models have been optimized using Hooke and Jeeves algorithm to minimize grain size and maximize the hardness.
文摘This article proposes a multidisciplinary design and optimization （MDO） strategy for the conceptual design of a multistage ground-based interceptor （GBI） using hybrid optimization algorithm, which associates genetic algorithm （GA） as a global optimizer with sequential quadratic programming （SQP） as a local optimizer. The interceptor is comprised of a three-stage solid propulsion system for an exoatmospheric boost phase intercept （BPI）. The interceptor＇s duty is to deliver a kinetic kill vehicle （KKV） to the optimal position in space to accomplish the mission of intercept. The modules for propulsion, aerodynamics, mass properties and flight dynamics are integrated to produce a high fidelity model of the entire vehicle. The propulsion module com- prises of solid rocket motor （SRM） grain design, nozzle geometry design and performance prediction analysis. Internal ballistics and performance prediction parameters are calculated by using lumped parameter method. The design objective is to minimize the gross lift off mass （GLOM） of the interceptor under the mission constraints and performance objectives. The proposed design and optimization methodology provide designers with an efficient and powerful approach in computation during designing interceptor systems.
文摘Once the disaster occurred, a huge amount of grain supply is needed from disaster area. Because of the short shelf life, grain is very strict with reserve environment and needed to rotate on a regular basis in the process of reserves. Considering the limitations of existing related research, this paper presented a facility location model for grain emergency network that incorporates inventory factors and rotation mechanism, and then designed genetic algorithm based on Matlab to solve the model. Finally we verified the feasibility and effectiveness of the algorithm by computational examples and presented the directions for future work.
基金provided by National Science Fundamental Key Project(40930526,40901041)Science Research Program of Global Change Research of China(Grant No.2010CB951404)
文摘In this paper, the significance and history of studying snow grain size is introduced. Based on the assumption that high reflectivity in the visible band and significant decreasing reflectivity of snow surface in the infrared band, the grain size of snow, spherical and non-spherical, is sensitive to changes in remote sensing retrieval foundation. Also, models and algorithms applied in current studies are reviewed, together with their advantages and disadvantages. In addition, in order to obtain retrieval accuracy, some factors that may affect grain size are also discussed, such as temperature, wavelength, arid particle shape, as well as method authentication.
文摘A description of a mathematical algorithm for simulating grain structures with straight and hyperbolic interfaces is shown. The presence of straight and hyperbolic interfaces in many grain structures of metallic materials is due to different solidification conditions, in- eluding different solidification speeds, growth directions, and delaying on the nucleation times of each nucleated node. Grain growth is a complex problem to be simulated; therefore, computational methods based on the chaos theory have been developed for this purpose. Straight and hyperbolic interfaces are between columnar and equiaxed grain structures or in transition zones. The algorithm developed in this work involves random distributions of temperature to assign preferential probabilities to each node of the simulated sample for nucleation according to previously defined boundary conditions. Moreover, more than one single nucleation process can be established in order to gen- erate hyperbolic interfaces between the grains. The appearance of new nucleated nodes is declared in sequences with a particular number of nucleated nodes and a number of steps for execution. This input information influences directly on the final grain structure （grain size and dislribution）. Preferential growth directions are also established to obtain equiaxed and columnar grains. The simulation is done using rou- tines for nucleation and growth nested inside the main function. Here, random numbers are generated to place the coordinates of each new nucleated node at each nucleation sequence according to a solidification probability. Nucleation and growth routines are executed as a func- tion of nodal availability in order to know if a node will be part of a grain. Finally, this information is saved in a two-dimensional computa- tional array and displayed on the computer screen placing color pixels on the corresponding position forming an image as is done in cellular automaton.
文摘For the great significance of the prediction of control parameters selected for hot-rolling and the evaluation of hot-rolling quality for the analysis of prod uction problems and production management, the selection of hot-rolling control parameters was studied for microalloy steel by following the neural network principle. An experimental scheme was first worked out for acquisition of sample data, in which a gleeble-1500 thermal simolator was used to obtain rolling temperature, strain, stain rate, and stress-strain curves. And consequently the aust enite grain sizes was obtained through microscopic observation. The experimental data was then processed through regression. By using the training network of BP algorithm, the mapping relationship between the hotrooling control parameters (rolling temperature, stain, and strain rate) and the microstructural paramete rs (austenite grain in size and flow stress) of microalloy steel was function appro ached for the establishment of a neural network-based model of the austeuite grain size and flow stress of microalloy steel. From the results of estimation made with the neural network based model, the hot-rolling control parameters can be effectively predicted.
文摘玉米育种过程中,灌浆期籽粒含水率检测时,通常需要脱粒,采集穗中间200粒为检测样本。为了保护亲本,避免破坏性检测,该研究提出一种基于近红外光谱的灌浆期玉米籽粒水分定量分析通用模型,用于灌浆期玉米籽粒水分的田间原位检测。首先构建GA-IRIV-DS光谱数据处理策略。利用遗传算法(genetic algorithm,GA)和迭代保留信息变量(iterative retention of information variables,IRIV)二次波长筛选方法,提取光谱数据中有效的水分变量信息,减小特征空间维度的同时提高模型预测精度;再结合直接校正算法(direct standardization,DS),降低预测样本与建模样本的差异性,将玉米灌浆期穗尖部籽粒光谱数据校正为中间200籽粒的光谱,使水分定量分析模型能够具备中间200籽粒和穗尖部籽粒2种检测样本的通用性。在GA-IRIV-DS光谱数据处理策略的基础上,构建基于偏最小二乘法(partial lpeast squares regression,PLSR)的水分定量分析通用模型。经过验证,GA-IRIV-DS光谱数据处理策略校正后的光谱差异性降低了59.4%。为了进一步验证GA-IRIV-DS光谱数据处理策略的有效性,分析了GA+IRIVN组合波长筛选提取光谱特征,并分别与全光谱、多种典型波长筛选方法结合DS方法构建基于偏最小二乘法(PLSR)的水分定量分析模型结果相比较。试验结果表明,两种样本预测集GA-IRIVN-DS-PLSR模型效果均优于全光谱和其他模型,中间籽粒样本和穗尖部籽粒样本的预测决定系数(R^(2))达到了0.9715和0.9012,均方根误差(RMSEP)较全光谱下降了80.10%和64.60%。证明基于GA-IRIVN-DS光谱数据处理策略建立的近红外光谱水分定量分析模型具有一定泛化能力,可以为玉米育种过程中,减少检测过程中的样本破坏和提高检测效率提供可行的参考方法。
文摘基于近红外偏最小二乘法(near-infrared partial least squares,NIR-PLS)开发了一种近红外光谱快速检测模型,用于快速、无损检测清蒸高粱糊化度。同时分析了白酒酿造生产关键指标相关性,以清蒸高粱糊化度为基础,结合清蒸高粱感官评价、出入窖糟醅理化、出酒率、基础酒理化及评分,利用自适应权重算法(adaptive weights,AW)建立了一种清蒸高粱蒸粮效果评价方法。该检测模型在预测清蒸高粱糊化度方面具有较高的相关性,模型预测值与建模参考值之间的决定系数R^(2)=0.9771。此外,蒸粮效果评价方法验证结果与经验丰富的酿酒师的感官评定相吻合。当75≤糊化度检测值≤80时,清蒸高粱糊化效果评价为优级;65≤糊化度检测值<75时,评价为一级;55<糊化度检测值<65或80<糊化度检测值<90时,评价为二级;糊化度检测值≥90或糊化度检测值≤55时,评价为不合格。该评价方法量化了白酒生产中清蒸高粱蒸粮效果的评定,将依赖经验的感官评估方式转化为标准化、数字化的手段,有助于加强生产过程和产品质量的可控性,减少粮食损耗。
