Experimental Measurement Techniques Research Articles

A reliable combustion strategy for a throttling-assisted supersonic combustor with flight Mach 7

As the flight Mach number increases, scramjet engines struggle to achieve stabilized combustion. In the present investigation, a reliable combustion strategy is developed for a kerosene-fueled supersonic combustor. Assisted by air throttling, this enables the combustor to operate efficiently at a flight Mach number of 7. Various experimental measurement techniques are used to capture the combustion process and flow characteristics. A three-dimensional numerical method based on the Reynolds-averaged Navier–Stokes equations is employed to analyse the effects of air throttling on the non-reacting and reacting flow fields. The whole combustion test is effectively divided into five processes covering the establishment of non-reacting flow, ignition, flame stabilization, and flameout. Analysis of the experimental and numerical flow fields indicates that, as the origin of the initial flame in the combustor, the aerodynamic compression induced by air throttling promotes the kerosene/air sub-mixing region. The main mixing process is enhanced by the arrangement of ramps and cavity, which contribute to effective multi-channel injection. Two combustion modes are observed, namely combined cavity shear-layer/recirculation stabilized combustion and jet-wake stabilized combustion. In the reacting flow field, the additional injection of throttling gas improves the thrust augmentation at the cost of reduced combustion intensity. The outlet combustion efficiency and total pressure recovery coefficient are found to decrease by 8.49% and 28.79%, respectively.

Desıgn of quantum-dot semiconductor optical amplifiers wıth near-zero linewidth enhancement factor

The linewidth enhancement factor (LWEF) of a semiconductor optical amplifier (SOA) quantifies refractive index fluctuations in the gain medium, which induce phase distortion in the amplified optical signal. Optoelectronic systems employing SOAs with high LWEFs often exhibit poor device stability and beam coherence. Thus, designing SOAs with low LWEF is imperative. Recently, Quantum-Dot (QD) SOAs have emerged as a solution for LWEF suppression due to quantum-confinement effects enabling tunability of the QD carrier density and emission frequency. In this study, we aim to design a composite active region comprised of a host medium and the embodied QDs, to explore the corresponding LWEF variation and propose the ultimate design strategy to achieve near-zero LWEF in QD SOAs for enhancing device stability and beam coherence. Our approach entails modeling the refractive index of the composite active region using effective medium approximation via Maxwell–Garnett mixing formulation. We then extensively tune key SOA parameters, including QD carrier density, QD emission frequency, and the collision-time constant of the carriers to uncover the optimal configuration for minimizing the LWEF. Based on empirical values, we have developed and validated a simple yet effective algorithm that precisely simulates LWEF behavior in response to changes in key QD SOA parameters. This approach offers a straightforward model for estimating LWEF variation, and its corresponding minimization in QD SOAs without requiring complex experimental measurement techniques.

Progress of Experimental Studies on Oblique Detonation Waves Induced by Hyper-Velocity Projectiles

Oblique detonation waves (ODWs) are hypersonic combustion phenomena induced by oblique shock waves. When applied to air-breathing engines, ODWs offer high thermal cycle efficiency, adaptability to a wide range of flight Mach numbers, and the advantage of a short combustion chamber, making them highly promising for hypersonic propulsion applications. Despite numerous numerical studies on the heat release and multi-wave flow mechanisms of ODWs, practical applications of oblique detonation engines (ODEs) remain limited due to several technical challenges. These challenges include generating the required high-velocity test environments, achieving effective fuel and oxidant mixing, and measuring the flow field structure in hyper-velocity and high-temperature flows. These limitations hinder the development of ODEs, underscoring the importance of experimental research, particularly for understanding the initiation and propagation mechanisms of ODWs. One of the primary experimental techniques involves inducing oblique detonation using high-velocity models. This method is extensively used to study the initiation process, shock structure, initiation criteria, and ODW propagation. It is advantageous because the state of the experimental mixture is controllable, and the model state can be precisely measured. This paper reviews studies on oblique detonation induced by hyper-velocity projectiles, presenting advances in experimental methods, detonation wave structures, unsteady processes, and initiation characteristics. Additionally, we discuss the deficiencies in existing studies, noting that the current measurement methods fall short of the requirements for observing the ODW initiation process, propagation process, and fine structure. The application of advanced combustion diagnostic techniques and the exploration of the relationship between initiation processes and criteria are crucial for advancing our understanding of ODW initiation and stabilization mechanisms. Finally, we summarize the current state of experimental facilities and measurement techniques, providing suggestions for future research on the measurement of shock waves and chemical reaction zones.

A comparison of machine learning methods for recovering noisy and missing 4D flow MRI data.

Experimental blood flow measurement techniques are invaluable for a better understanding of cardiovascular disease formation, progression, and treatment. One of the emerging methods is time-resolved three-dimensional phase-contrast magnetic resonance imaging (4D flow MRI), which enables noninvasive time-dependent velocity measurements within large vessels. However, several limitations hinder the usability of 4D flow MRI and other experimental methods for quantitative hemodynamics analysis. These mainly include measurement noise, corrupt or missing data, low spatiotemporal resolution, and other artifacts. Traditional filtering is routinely applied for denoising experimental blood flow data without any detailed discussion on why it is preferred over other methods. In this study, filtering is compared to different singular value decomposition (SVD)-based machine learning and autoencoder-type deep learning methods for denoising and filling in missing data (imputation). An artificially corrupted and voxelized computational fluid dynamics (CFD) simulation as well as in vitro 4D flow MRI data are used to test the methods. SVD-based algorithms achieve excellent results for the idealized case but severely struggle when applied to in vitro data. The autoencoders are shown to be versatile and applicable to all investigated cases. For denoising, the in vitro 4D flow MRI data, the denoising autoencoder (DAE), and the Noise2Noise (N2N) autoencoder produced better reconstructions than filtering both qualitatively and quantitatively. Deep learning methods such as N2N can result in noise-free velocity fields even though they did not use clean data during training. This work presents one of the first comprehensive assessments and comparisons of various classical and modern machine-learning methods for enhancing corrupt cardiovascular flow data in diseased arteries for both synthetic and experimental test cases.

Simultaneous measurement of velocity field of liquid–solid particle flow in pipelines and analysis of flow characteristics

The liquid–solid particle flow within a horizontal pipeline is a typical particle-laden flow. The interplay between loaded particles and carrier phase engenders significant complexities in the dynamic behavior of such flows. We investigated the dynamics of a liquid–solid particle flow featuring dilute, slightly buoyant, hundred-micron-sized spherical particles fully suspended in the turbulent flow in a pipe, where Re is 7038. Cases with solid volume fractions of 0, 2.67 × 10-4, 5.33 × 10-4, 8.00 × 10-4, 1.07 × 10-3 and 1.33 × 10-3 were considered in this study. Experimental measurement techniques were utilized to acquire images of particles in the two-phase flow across the entire flow field via optical field feedback. Particle image velocimetry (PIV) and particle tracking velocimetry (PTV) were employed to simultaneously obtain liquid-phase velocity fields and particle trajectories. This approach allowed for a comprehensive depiction of the velocity field of each phase. Subsequently, a detailed explanation and analysis of the flow characteristics of the liquid–solid particle flow were provided based on the distribution of macroscopic velocity fields, the microscopic vorticity field, particle velocity vectors, and velocity slip. As a result, it was found that with the addition of solid particles and an increase in volume concentration, the drag effect of the solid phase and the trend of accumulation near the lower wall caused a decrease in the liquid phase velocity profile and deformation of the parabolic shape. In the liquid–solid particle flow with a volume concentration of 1.33 × 10-3, compared to the single-liquid phase flow, the standard deviation of velocity in the central region increased from 0.0097 m/s to 0.0159 m/s, and in the near-wall region, it increased from 0.0257 m/s to 0.0347 m/s, representing increases of 1.54 times and 1.26 times respectively. The proportion of medium vortices increased from 17 % to 30 %, nearly doubling. This study actively explores the concurrent measurement and flow characteristics of liquid–solid particle flow.

Compact Spinning with Different Fibre Types: An Experimental Investigation on Yarn Properties in the Condensing Zone with 3D-Printed Guiding Device

Abstract The lattice apron-based compact spinning system is a form of pneumatic compact spinning that employs airflow to condense fibres into a bundle, enhancing the yarn’s attributes. To explore the airflow dynamics in pneumatic compact spinning, researchers primarily employ traditional theoretical approaches, experimental measurement techniques, and computational fluid dynamics (CFD) methods. In our previous research, we utilized CFD to observe the airflow patterns in pneumatic compact spinning. In this study, we implemented experimental measurement techniques to assess the impact of a 3D-printed guiding device (B-type) on yarn properties. We tested different fibre types in the condensing zone of the compact spinning system with a lattice apron. We used three types of roving to spin the yarn: pure cotton, cotton/polyester (80/20), and polyester/viscose (65/35). The findings revealed that yarns spun using the guiding device exhibited superior strength, hairiness, and evenness compared to those spun without the device.

A Pioneering Review on Quantitative Analysis of the Effect of Macromolecular Crowding on Drug Transport and Release: Current Implications

The intricate interplay of macromolecules within biological systems significantly influences the behavior of therapeutic agents, making the understanding of macromolecular crowding crucial for the advancement of drug delivery technologies. This review article provides a comprehensive analysis of the effects of macromolecular crowding on drug transport and release, emphasizing its quantitative impact and current implications in the field. Macromolecular crowding, characterized by the dense packing of proteins, nucleic acids, and other polymers in cellular environments, alters key biophysical properties, such as viscosity, diffusion rates, and molecular interactions. These changes critically affect the pharmacokinetics and pharmacodynamics of drugs, presenting both challenges and opportunities for therapeutic design and application. The article delves into the theoretical foundations of macromolecular crowding, grounded in thermodynamics and statistical mechanics, to elucidate how such conditions modulate drug behavior. Through an integrated review of empirical research and advanced simulation models, it highlights innovative strategies to harness crowding effects for optimizing drug delivery systems. The discussion extends to the evaluation of experimental methodologies and measurement techniques, including spectroscopy and imaging that are pivotal in quantifying the implications of crowding. This pioneering review not only synthesizes current research but also identifies gaps in knowledge and proposes directions for future investigation. It aims to serve as a vital resource for researchers and practitioners, fostering the development of more effective drug delivery mechanisms by leveraging the nuanced understanding of macromolecular crowding. This work underscores the potential of this underexplored area to significantly influence the next generation of pharmaceutical formulations and therapeutic interventions.

Degradation mechanism of measuring performance of optical particle counter under temperature-pressure coupling effect

To investigate the degradation mechanism of measuring the performance of an optical particle counter (OPC) under temperature-pressure coupling, this study first establishes a theoretical calculation model of gas refractive index and then elucidates the comprehensive influence mechanism of temperature and pressure on gas optical properties. Furthermore, the experimental measurement technique and measuring device for gas refractive index are built. By comparing the theoretical and experimental results in the temperature range of 48 °C–560 °C and the pressure range of 0.9–4.6 MPa, the difference between the two errors is just 0.05%, indicating the accuracy of the theoretical model of the refractive index of gas. Secondly, a dynamic model of optical measurement volume (OMV) under high-temperature and high-pressure conditions was established using geometrical optics theory, and the impacts of gas temperature and pressure variations on OPC measurement performance were investigated. The gas temperature (100 °C–1000 °C) and pressure (1–4.6 MPa) are shown to have opposing effects on the OMV, with gas pressure being more relevant. Finally, in order to eliminate the effect of gas refractive index change on the optical measurement performance of OPC, a parallel light model is proposed to solve the problem of the degradation of OPC measurement performance under temperature and pressure coupling conditions.

Melting point of iron at high pressure: An assessment of uncertainties and effect of electronic temperature

An accurate calculation of the melting point of iron at various pressures in the Earth's core is important for understanding the core structure, geodynamo, and the Earth's history. Previous studies have assessed the melt line of iron at these extreme conditions using various experimental measurement techniques as well as both ab initio and classic molecular dynamics simulations. However, experimental measurements have uncertainties up to several hundred Kelvin, and inconsistencies remain among simulation results. In this work, we propose an iterative framework that couples density functional theory (DFT) calculations and molecular dynamics simulations performed using an ensemble of interatomic potentials to assess the effect of electronic temperature on the melting point. We systematically validate the potentials by comparing lattice constants and phonon dispersion curves at 0 K and enthalpy differences between liquid and HCP, FCC, BCC phases of iron close to the melt line at 300 GPa with DFT. Our results show that HCP iron melts at 6144 K (at 300 GPa), BCC phase is thermodynamically unstable, and FCC is metastable at this temperature. The melting points of FCC and BCC phases at 300 GPa are 5858 and 5647 K, respectively.

Single-shot fast cinematic imaging during merging process of multiple electron filaments in electrostatic potential well.

For the first time, details of the spatial and temporal acceptable evolution of the merging process of co-rotating electron vortices in a potential well are successfully captured using a "single-shot method" with a high temporal resolution of 10 µs. Four-electron filaments are trapped inside the Beam eXperiment-Upgrade linear trap [H. Himura, Nucl. Instrum. Methods Phys. Res. A 811, 100 (2016)] with a uniform axial magnetic field and co-axial multi-ring electrodes. Images of non-emitting electron filaments are captured using a high-speed camera with up to 1 000 000fps, a microchannel plate, a fast-decay phosphor screen of which fluorescence duration is 0.15 µs, and a super fine metallic mesh with an open area ratio of 89%. Images captured every 10 µs clearly show the growth of multiple short-wave instabilities in the wing trailing electron vortices. The experimental methods and measurement techniques presented in this paper can contribute to revealing exactly how small vortices evolve into a large structure or turbulence in a potential well through complex processes.

Subcooled forced convection boiling flow measured using high-resolution techniques at the COSMOS-L facility and accompanying CFD simulation employing an interface-tracking scheme

This paper describes state-of-the-art experimental measurement techniques and computational fluid dynamics methods applied to subcooled forced convection boiling flow at 2-3 bar, both featuring high spatial- and time-resolution measurements. The objectives are: (i) to provide the measured boiling flow data, e.g. average and RMS profiles of axial and radial velocities and bubble size distributions, and (ii) to evaluate the capabilities of state-of-the-art numerical simulation techniques to model the observed phenomena, by comparison between measured data and numerical prediction. In the experiment, the bubble velocities in the axial and radial directions were measured using laser Doppler anemometry, and the bubble size was estimated by a shadowgraphy method. The simulation results, incorporating an interface capturing technique, showed good agreement with measurement in terms of the wall temperature and axial velocity, but underestimation of the radial velocity, and overestimation of bubble sizes. The paper shows that the discrepancies between measurement and simulation may be traced to: (i) the uncertainties in the nucleation site density model; (ii) too coarse a grid being adopted, which is not able to resolve the thermal boundary layer around the bubbles; and (iii) spurious numerical bubble coalescence, a feature not seen in the experiment. The mechanism of bubble lift-off from the hot surface, without any sliding motion, as observed in the experiment, is discussed in detail, based on the simulation results, and the condensation on the bubble cap as the bubble is ‘sucked’ into the bulk flow is also examined.

Thermal Conductivity Enhancement of Polymeric Composites Using Hexagonal Boron Nitride: Design Strategies and Challenges.

With the integration and miniaturization of chips, there is an increasing demand for improved heat dissipation. However, the low thermal conductivity (TC) of polymers, which are commonly used in chip packaging, has seriously limited the development of chips. To address this limitation, researchers have recently shown considerable interest in incorporating high-TC fillers into polymers to fabricate thermally conductive composites. Hexagonal boron nitride (h-BN) has emerged as a promising filler candidate due to its high-TC and excellent electrical insulation. This review comprehensively outlines the design strategies for using h-BN as a high-TC filler and covers intrinsic TC and morphology effects, functionalization methods, and the construction of three-dimensional (3D) thermal conduction networks. Additionally, it introduces some experimental TC measurement techniques of composites and theoretical computational simulations for composite design. Finally, the review summarizes some effective strategies and possible challenges for the design of h-BN fillers. This review provides researchers in the field of thermally conductive polymeric composites with a comprehensive understanding of thermal conduction and constructive guidance on h-BN design.

Rotating detonation combustor performance informed through a novel megahertz-rate stagnation pressure measurement

An experimental stagnation pressure measurement technique is presented for a rotating detonation combustor (RDC). Schlieren imaging enables rotating detonation wave passage to be correlated with oscillations observed in the under-expanded exhaust plume. By measuring the spatiotemporal variation in exhaust plume divergence angle, stagnation pressure measurements of the RDC were acquired at a rate of 1 MHz. Combustor mass flux was varied between 202 and 783 kg/m2s, producing equivalent available pressures (EAPs) in the range of 3.42–13.5 bar. Time-averaged stagnation pressure measurements gathered using this technique were in agreement with the measured EAP within ±1.5%. Time-resolved stagnation pressure measurements allow for the pressure ratio produced across detonation wave cycles to be determined. For the conditions tested, detonation pressure ratios and wave speeds decreased while increasing the mean operating pressure of the combustor. Numerical modeling of the conditions tested indicates that the decrease in pressure ratio and wave speed is a result of elevated levels of combustion prior to the detonation wave arrival (i.e., “preburning”). Simultaneous OH* chemiluminescence measurements within the combustion chamber show an increase in preburned heat release relative to detonative heat release for increasing operating pressures of the RDC, in agreement with the results of the numerical model. Modeled chemical kinetic timescales decrease by approximately the same magnitude by which the preburning mass fraction increased in the range of operating pressures tested, suggesting that the faster reaction rates associated with higher pressure combustion may be the reason for increased preburning within the combustor.

Probing Polaron Clouds by Rydberg Atom Spectroscopy.

In recent years, Rydberg excitations in atomic quantum gases have become a successful platform to explore quantum impurity problems. A single impurity immersed in a Fermi gas leads to the formation of a polaron, a quasiparticle consisting of the impurity being dressed by the surrounding medium. With a radius of about the Fermi wavelength, the density profile of a polaron cannot be explored using insitu optical imaging techniques. In this Letter, we propose a new experimental measurement technique that enables the insitu imaging of the polaron cloud in ultracold quantum gases. The impurity atom induces the formation of a polaron cloud and is then excited to a Rydberg state. Because of the mesoscopic interaction range of Rydberg excitations, which can be tuned by the principal numbers of the Rydberg state, atoms extracted from the polaron cloud form dimers with the impurity. By performing first principle calculations of the absorption spectrum based on a functional determinant approach, we show how the occupation of the dimer state can be directly observed in spectroscopy experiments and can be mapped onto the density profile of the gas particles, hence providing a direct, real-time, and insitu measure of the polaron cloud.

Influence of co-deposition modification on mode I and II interlaminar toughness of epoxy laminates interleaved with waste textiles using experimental measurement and finite element technique

Interlaminar delamination has been a persistent problem that restricts the ability of fiber reinforced laminated composites under applied load. The influence of polyethyleneimine-catechol (PEI-CCh) co-deposition modification on the mode I (GIC) and II interlaminar fracture toughness (GIIC) of plain glass fiber fabric reinforced epoxy composites (PGFRECs) were discussed using double cantilever beam (DCB) and end notch flexural (ENF) tests. It was found that interfacial properties of PET/epoxy and PET/cotton/epoxy interfaces were substantially improved after co-deposited modification, which laid a solid foundation for enhancing the resistance to interlaminar delamination. GIC and GIIC in platform of crack propagation greatly increased with the introduction of co-deposition layer. The fracture surfaces of delaminated failure specimens were observed by scanning electron microscope. The higher propagation fracture toughness for co-deposition modified PGFRECs is due to the anchoring effect of functional layer combining waste fabrics with epoxy matrix to provide favorable stress transfer channel prior to macroscopic crack formation. In regard to the delamination crack, new crack generation and bridge fiber failure mainly dominated the mode I crack extension process, while zigzag sections were particularly common for mode II fracture specimens.

Correlation of work function and stacking fault energy through Kelvin probe force microscopy and nanohardness in dilute α-magnesium

Electronic interactions of the Group 2A elements with magnesium have been studied through the dilute solid solutions in binary Mg-Ca, Mg-Sr and Mg-Ba systems. This investigation incorporated the difference in the ‘Work Function’ (ΔWF) measured via Kelvin Probe Force Microscopy (KPFM), as a property directly affected by interatomic bond types, i.e. the electronic structure, nanoindentation measurements, and Stacking Fault Energy values reported in the literature. It was shown that the nano-hardness of the solid-solution α-Mg phase changed in the order of Mg-Ca>Mg-Sr>Mg-Ba. Thus, it was shown, by also considering the nano-hardness levels, that SFE of a solid-solution is closely correlated with its ‘Work Function’ level. Nano-hardness measurements on the eutectics and ΔWF difference between eutectic phases enabled an assessment of the relative bond strength and the pertinent electronic structures of the eutectics in the three alloys. Correlation with ΔWF and at least qualitative verification of those computed SFE values with some experimental measurement techniques were considered important as those computational methods are based on zero Kelvin degree, relatively simple atomic models and a number of assumptions. As asserted by this investigation, if the results of measurement techniques can be qualitatively correlated with those of the computational methods, it can be possible to evaluate the electronic structures in alloys, starting from binary systems, going to ternary and then multi-elemental systems. Our investigation has shown that such a qualitative correlation is possible. After all, the SFE values are not treated as absolute values but rather become essential in comparative investigations when assessing the influences of alloying elements at a fundamental level, that is, free electron density distributions. Our study indicated that the principles of ‘electronic metallurgy’ in developing multi-elemental alloy systems can be followed via practical experimental methods, i.e. ΔWF measurements using KPFM and nanoindentation.

Swirling flow of two immiscible fluids in a cylindrical container: Lattice Boltzmann and volume-of-fluid study

An experimental and numerical study of a multicomponent swirl flow of a liquid in a closed cylinder is carried out for various values of the relative cylinder elongation and the Reynolds number. The experimental technique for flow characteristics measurement is based on the PIV (particle image velocimetry) technique. To study the flow characteristics in detail, we simulated the problem numerically using the Palabos and Basilisk software open-source packages. The current implementation of the Palabos package uses the LBM (lattice Boltzmann method) approach, in which the collision integral is determined by the MRT (multiple-relaxation-time) approximation, and the intercomponent interaction is established according to the Shan–Chen pseudopotential approximation. The Basilisk package uses VOF (volume-of-fluid) approach to approximate the fluid interface. In this paper, for the first time, the data considering the emergence conditions for the zone of axial isolated recirculation in a multicomponent vortex flow were obtained at different viscosity ratios of two fluids. It is shown that with a decrease in the viscosities ratio, the recirculation zone existence curve shifts closer to that corresponding to the case of a one-component flow. In the course of numerical analysis, we found that both numerical implementations of this problem describe flow characteristics with high accuracy. Both methods recreate the recirculation zone on the cylinder axis observed experimentally. However, the velocity shift on the interface is observed only in the LBM approach.

An advanced laboratorial measurement technique of scour topography based on the fusion method for 3D reconstruction

Local scour is a phenomenon that occurs around water-blocking structures such as bridge piers, pile foundations, and pipelines, which threatens seriously the safety of structures. The laboratory test based on wave and flow tanks is an effective way investigating the local scour around piles. The measurement of scour depth and topography is an important basis for this type of experimental analysis, which can help the researchers to perform a quantitative analysis on the scour mechanism. The conventional measurement methods in scouring experiments have limitations in terms of operational efficiency, measurement range, and cost. Therefore, an advanced experimental measurement technique based on the RGB-D sensor and the 3D reconstruction algorithm was proposed in this work to provide the full topography information around target zone after scour. Experiments applying this 3D reconstruction method were conducted for the practical scour tests. The impact of water on the application of this technique was discussed as well. The results showed that the new technique has good accuracy in scour topography description and scour depth measurement. This work provides a new measure technique for laboratory scour tests. The proposed method has a broad application prospect in measurements for such experimental scenes.

A simple transformation for switching between the stochastic responses in different systems

The progress gained inside the structural and acoustic similitudes makes possible to some extent to change the scales (sizes, materials, topologies, etc.) of many engineering systems. Here, an exact transformation defined by using the Betti theorem, is invoked for the analysis of the stochastic response of the elastic structures wetted by the wall pressure distribution due to a turbulent boundary layer. This kind of response can be severely challenging for both the numerical approaches and the experimental measurement techniques. The transformation, named VOODOO (a versatile offset operator for the discrete observation of objects), is here used for predicting the stochastic responses in two different plates. The method allows connecting the degrees of freedom (in a discrete number of points) of two completely different systems through a matrix operator: if the excitation/response pints are located/evaluated at the points used for building this matrix, the transformation is exact. In the present case, the stochastic pressure loads act on the whole systems and thus the computed responses will be associated to errors: the analysis of these errors is the actual focus.

Establishment and validation of a relationship model between nozzle experiments and CFD results based on convolutional neural network

The acquisition of experimental data in a supersonic wind tunnel often faces challenges of complexity and high costs. Furthermore, there are limitations in the control of experimental conditions and measurement techniques. In this study, experiments were conducted on the start-up and shutdown processes of a single expansion ramp nozzle (SERN), and a dataset was established in conjunction with computational fluid dynamics (CFD). By utilizing experimental data and CFD simulation results, we employed a deep learning-based approach, utilizing one-dimensional convolutional neural networks (CNN), to establish a relationship model between the experimental and CFD results, with the aim of using CFD results to predict experimental outcomes. We provide detailed descriptions of the experimental methods, numerical simulation methods, and CNN model, and conduct training and testing of the model. The results demonstrate that the CNN model is capable of accurately predicting the wall pressure distribution of the SERN, with low prediction errors. In interpolation and extrapolation cases, the model exhibits good accuracy and generalization ability, with coefficients of determination above 96%. Compared to CFD calculations, the CNN model proves to be more reliable and accurate in predicting SERN performance. Additionally, we establish a comparative model that does not utilize CFD data to verify the superiority of the proposed CNN model. The results show that the CNN model with CFD data improves performance on average by 14%. This approach reduces reliance on experiments to a certain extent, lowering experimental costs and complexity. It not only saves the resources and time required for experiments but also compensates for the limitations in controlling experimental conditions and measurement techniques. Therefore, this research provides a viable solution to overcome the challenges and limitations of acquiring experimental data.