6results about How to "Strong guidance" patented technology

This invention relates to a SCC mix design method and system based on the shear strength theory of cement paste. Its core lies in establishing a cement paste shear strength prediction model. This model quantitatively evaluates the shear strength of the cement paste under a proposed mix proportion and compares it with a pre-determined reasonable range. Then, through iterative adjustments to the cementitious material composition and water-cement ratio, the shear strength of the cement paste falls within the target range, thereby simultaneously optimizing the paste rheology and determining the final mix proportion. This invention achieves complete quantitative design from aggregate to paste, economically and efficiently preventing SCC segregation and maximizing the use of auxiliary cementitious materials to reduce the cost of self-compacting concrete.

This invention belongs to the field of engine turbocharger testing technology and discloses a method and system for evaluating the transient response of engine turbochargers. The method includes: test preparation, operating condition setting, transient excitation and data acquisition, calculation of speed increment time, calculation of intake pressure to establish efficiency indicators, and two-dimensional diagnostic evaluation. This invention effectively solves the technical problem that existing evaluation parameters cannot distinguish the root cause of response lag, and has advantages such as accurate positioning and strong guidance. It is particularly suitable for the research and optimization of turbocharger systems with stringent transient response requirements, such as hydrogen fuel cell internal combustion engines.

This invention relates to the field of yield strength calculation technology, and in particular to a method for calculating the yield strength of 42CrMo steel used in engineering machinery. The method involves establishing a dimensionless model through data fitting between the yield strength Y1 and the quenching temperature X1, tempering temperature X2, and the mass percentage of Mn element X3: Y1 = 5479 - 2.81X1 - 4.643X2 + 889X3. This invention can accurately reflect the quantitative relationship between the heat treatment process parameters of 42CrMo steel, especially the tempering temperature and the yield strength, enabling the prediction of yield strength. This allows engineers to accurately predict the final properties of the material when formulating the heat treatment process, and to actively and accurately control the yield strength of the material by adjusting the process parameters.

The application provides a design method of a reverseable gas turbine sliding bearing tile oil supply device, which comprises the following steps: S1, giving design input; S2, determining the number n of oil supply pipes; S3, determining the diameter phi of the oil supply pipes; S4, determining the positioning size L and alpha of the nozzle; S5, determining the diameter d and the spacing L of the nozzle; S6, calculating the oil flow; and S7, processing the reverseable gas turbine sliding bearing tile oil supply device meeting the design. K The design method scheme is reasonable, the design flow is clear, the guidance is strong, and the efficiency of the reverseable gas turbine sliding bearing tile oil supply device is greatly improved. The application is used in the domestic reverseable gas turbine sliding bearing design for the first time, and has very important reference value in the future gas turbine sliding bearing design.

This invention relates to the fields of clinical laboratory medicine and artificial intelligence, and provides a risk prediction method and device based on machine learning for clinical mass spectrometry. The risk prediction method includes: defining N+M dimensions of features based on a liquid chromatography-tandem mass spectrometry system to obtain an N+M dimension feature vector structure; obtaining a virtual training dataset based on the N+M dimension feature vector structure, acquiring parameter values ​​of each dimension of the current batch through a data acquisition interface, and assembling them into N+M dimension feature vector data; performing format verification and invalid value filtering on the N+M dimension feature vector data using the N+M dimension feature vector structure to obtain a feature matrix; and obtaining a standardized real-time risk score based on the feature matrix and a trained fusion-integrated risk prediction model. This invention utilizes a machine learning model to uncover the complex nonlinear relationship between configuration parameters and dynamic parameters, thereby achieving more accurate and forward-looking risk warnings than traditional single-threshold methods.

The invention discloses a coal bed gas horizontal well drilling fluid plugging performance evaluation method, and relates to the technical field of oil and gas exploitation, coal dust and coal gangue returned by a coal bed gas horizontal well are taken, dried and crushed, a cementing agent is added, a glue-containing mixture is prepared, and curing and cutting are performed to obtain a coal rock plate or a coal rock plate with microcracks; a coal rock plate is used as a filtration medium of the plugging instrument, and the measured plugging filtration loss and the plugging filtration loss reduction rate are used as evaluation indexes for evaluating the coal rock plugging anti-collapse performance of the drilling fluid; a coal rock plate with micro-cracks is used as a filtration medium of the plugging instrument, and the measured plugging filtration loss and the plugging filtration loss reduction rate are used as evaluation indexes for evaluating the plugging anti-collapse performance of the drilling fluid on coal rock with micro-crack development, so that the anti-collapse performance of horizontal well water-based drilling fluid such as coal bed gas and the like can be reflected more reliably, quickly and accurately; the method is used for guiding safe and rapid construction of horizontal wells easy to collapse, such as deep coal bed gas and carbonaceous mudstone.