articles+ search results

Intelligent transportation systems, Joint detection and tracking, Global correlation network, End-to-end tracking, Ocean engineering, TC1501-1800, Mechanical engineering and machinery, and TJ1-1570

Abstract Environment perception is one of the most critical technology of intelligent transportation systems (ITS). Motion interaction between multiple vehicles in ITS makes it important to perform multi-object tracking (MOT). However, most existing MOT algorithms follow the tracking-by-detection framework, which separates detection and tracking into two independent segments and limit the global efficiency. Recently, a few algorithms have combined feature extraction into one network; however, the tracking portion continues to rely on data association, and requires complex post-processing for life cycle management. Those methods do not combine detection and tracking efficiently. This paper presents a novel network to realize joint multi-object detection and tracking in an end-to-end manner for ITS, named as global correlation network (GCNet). Unlike most object detection methods, GCNet introduces a global correlation layer for regression of absolute size and coordinates of bounding boxes, instead of offsetting predictions. The pipeline of detection and tracking in GCNet is conceptually simple, and does not require complicated tracking strategies such as non-maximum suppression and data association. GCNet was evaluated on a multi-vehicle tracking dataset, UA-DETRAC, demonstrating promising performance compared to state-of-the-art detectors and trackers.

Electric field, Magnetic field, Microstructures, Mechanical properties, Solid metals, Ocean engineering, TC1501-1800, Mechanical engineering and machinery, and TJ1-1570

Abstract An external electric or magnetic field can transfer high-intensity energy directly to the electronic scale of materials, and change the spin, energy level arrangement and trajectory of electrons. These changes produce tremendous and profound impacts on the microstructure and mechanical properties of metal materials, which may be impossible with traditional technologies. This paper reviews the effects of electric or magnetic field on the microstructures of solid metals including phase transformation, precipitation, recrystallization, dislocations and so on. Based on the existing research results, the mechanisms of these effects have been discussed. Additionally, some typical applications of electric and magnetic treatments on solid metals have been described and the challenges in this field have also been discussed.

Multibody dynamics, 3D revolute joint, Wear prediction, Digital image correlation, Ocean engineering, TC1501-1800, Mechanical engineering and machinery, and TJ1-1570

Abstract The existence of the relative radial and axial movements of a revolute joint’s journal and bearing is widely known. The three-dimensional (3D) revolute joint model considers relative radial and axial clearances; therefore, the freedoms of motion and contact scenarios are more realistic than those of the two-dimensional model. This paper proposes a wear model that integrates the modeling of a 3D revolute clearance joint and the contact force and wear depth calculations. Time-varying contact stiffness is first considered in the contact force model. Also, a cycle-update wear depth calculation strategy is presented. A digital image correlation (DIC) non-contact measurement and a cylindricity test are conducted. The measurement results are compared with the numerical simulation, and the proposed model’s correctness and the wear depth calculation strategy are verified. The results show that the wear amount distribution on the bearing’s inner surface is uneven in the axial and radial directions due to the journal’s stochastic oscillations. The maximum wear depth locates where at the bearing’s edges the motion direction of the follower shifts. These findings help to seek the revolute joints’ wear-prone parts and enhance their durability and reliability through improved design.

Digital twin, Digital twin shop-floor, Synchronization in digital twin shop-floor, Synchronization mechanism, Satellite assembly shop-floor, Ocean engineering, TC1501-1800, Mechanical engineering and machinery, and TJ1-1570

Abstract In recent years, as a promising way to realize digital transformation, digital twin shop-floor (DTS) plays an important role in smart manufacturing. The core feature of DTS is the synchronization. How to implement and maintain the synchronization is critical for DTS. However, there is still a lack of a common definition for synchronization in DTS. Besides, a systematic synchronization mechanism for DTS is strongly needed. This paper first summarizes the definition and requirements of synchronization in DTS, to clarify the understanding of synchronization in DTS. Then, a 5M synchronization mechanism for DTS is proposed, where 5M refers to multi-system data, multi-fidelity model, multi-resource state, multi-level state, and multi-stage operation. As a bottom-up synchronization mechanism, 5M synchronization mechanism for DTS has the potential to support DTS to achieve and maintain physical-virtual state synchronization, and to realize operation synchronization of DTS. The implementation methods of 5M synchronization mechanism for DTS are also introduced. Finally, the proposed synchronization mechanism is validated in a digital twin satellite assembly shop-floor, which proves the effectiveness and feasibility of the mechanism.

Curved surface, Five-axis machining, Dimension reduction and mapping, Milling force, Dynamics, Ocean engineering, TC1501-1800, Mechanical engineering and machinery, and TJ1-1570

Abstract The equipment used in various fields contains an increasing number of parts with curved surfaces of increasing size. Five-axis computer numerical control (CNC) milling is the main parts machining method, while dynamics analysis has always been a research hotspot. The cutting conditions determined by the cutter axis, tool path, and workpiece geometry are complex and changeable, which has made dynamics research a major challenge. For this reason, this paper introduces the innovative idea of applying dimension reduction and mapping to the five-axis machining of curved surfaces, and proposes an efficient dynamics analysis model. To simplify the research object, the cutter position points along the tool path were discretized into inclined plane five-axis machining. The cutter dip angle and feed deflection angle were used to define the spatial position relationship in five-axis machining. These were then taken as the new base variables to construct an abstract two-dimensional space and establish the mapping relationship between the cutter position point and space point sets to further simplify the dimensions of the research object. Based on the in-cut cutting edge solved by the space limitation method, the dynamics of the inclined plane five-axis machining unit were studied, and the results were uniformly stored in the abstract space to produce a database. Finally, the prediction of the milling force and vibration state along the tool path became a data extraction process that significantly improved efficiency. Two experiments were also conducted which proved the accuracy and efficiency of the proposed dynamics analysis model. This study has great potential for the online synchronization of intelligent machining of large surfaces.

ais data, real ship, hydrodynamic coefficient, support vector regression, parameter identification, Ocean engineering, and TC1501-1800

In response to the complexity and time demands of conventional methods for estimating the hydrodynamic coefficients, this study aims to revolutionize ship maneuvering analysis by utilizing automatic identification system (AIS) data and the Support Vector Regression (SVR) algorithm. The AIS data were collected and processed to remove outliers and impute missing values. The rate of turn (ROT), speed over ground (SOG), course over ground (COG) and heading (HDG) in AIS data were used to calculate the rudder angle and ship velocity components, which were then used as training data for a regression model. The accuracy and efficiency of the algorithm were validated by comparing SVR-based estimated hydrodynamic coefficients and the original hydrodynamic coefficients of the Mariner class vessel. The validated SVR algorithm was then applied to estimate the hydrodynamic coefficients for real ships using AIS data. The turning circle test wassimulated from calculated hydrodynamic coefficients and compared with the AIS data. The research results demonstrate the effectiveness of the SVR model in accurately estimating the hydrodynamic coefficients from the AIS data. In conclusion, this study proposes the viability of employing SVR model and AIS data for accurately estimating the hydrodynamic coefficients. It offers a practical approach to ship maneuvering prediction and control in the maritime industry.

digital transformation, small, medium, and large companies collaboration, value chain, master plan, Ocean engineering, and TC1501-1800

In the shipbuilding and marine industry, digital transformation activities are promoted primarily by large shipyards. However, bottlenecks are observed across value chains, and digital transformation effects are reducing because of the cost and technical challenges encountered by supplies. In this study, we proposed a win-win cooperation model for large, small, and medium-sized companies using digital transformation based on the characteristics of the shipbuilding and marine industry through case studies. We investigated the digital transformation progress in German and Korean small and medium-sized enterprises (SMEs). In addition, we identified information-sharing methods and management challenges encountered in enterprise resource planning and manufacturing execution systems in the collaboration process of pipes, panels, blocks, etc. of SMEs that are suppliers of a Korean shipyard, and clarified communication by building a platform based on a common format between shipyards and suppliers. Further, we proposed a standard model of a digital transformation system for enhancing the collaboration between large companies and suppliers and proposed a basic plan including strategies to efficiently and effectively build a digital transformation system based on the standard model.

energy efficiency of ships, fuel consumption, ship hull condition, marine propeller roughness, navigation environment condition, Ocean engineering, and TC1501-1800

The fuel consumption of marine diesel engines holds paramount importance in contemporary maritime transportation and shapes energy efficiency strategies of ocean-going vessels. Nonetheless, a noticeable gap in knowledge prevails concerning the influence of ship hull conditions and propeller roughness on fuel consumption. This study bridges this gap by utilizing artificial intelligence techniques in Matlab, particularly convolutional neural networks (CNNs) to comprehensively investigate these factors. We propose a time-series prediction model that was built on numerical simulations and aimed at forecasting ship hull and propeller conditions. The model's accuracy was validated through a meticulous comparison of predictions with actual ship-hull and propeller conditions. Furthermore, we executed a comparative analysis juxtaposing predictive outcomes with navigational environmental factors encompassing wind speed, wave height, and ship loading conditions by the fuzzy clustering method. This research's significance lies in its pivotal role as a foundation for fostering a more intricate understanding of energy consumption within the realm of maritime transport.

finite element analysis, marine nuclear reactor operation, material property variation, neutron irradiation, stiffened plated structure, structural responses, Ocean engineering, and TC1501-1800

As the regulations on greenhouse gas emissions at sea become strict, efforts are being made to minimize environmental pollutants emitted from fossil fuels used by ships. Considering the large sizes of ships in conjunction with securing stable supplies of environment-friendly energy, interest in nuclear energy to power ships has been increasing. In this study, the neutron irradiation that occurs during the nuclear reactor operation and its effect on the structural responses of the stiffened-plate structures are investigated. This is done by changing the material properties of DH36 steel according to the research findings on the neutron-irradiated steels and then performing the structural response analyses of the structures using analytical and finite-element numerical solutions. Results reveal the influence of neutron irradiation on the structural responses of the structures. It is shown that both the strength and stiffness of the structures are affected by the neutron-irradiation phenomenon as their maximum flexural stress and deflection are increased with the increase in the amount of neutron irradiation. This implies that strength and stiffness need to be considered in the design of ships equipped with marine nuclear reactors.

anti-icing, surface heating element, heating coil, heated walkway, cfd, heat transfer, Ocean engineering, and TC1501-1800

While melting glaciers due to global warming have facilitated the development of polar routes, Arctic vessels require reliable anti-icing methods to prevent hull icing. Currently, the existing anti-icing method, i.e., the heating coil method, has disadvantages, such as disconnection and power inefficiency. Therefore, a carbon nanotube-based surface heating element method was developed to address these limitations. In this study, the numerical analysis of the surface heating element method was performed using ANSYS. The numerical analysis included conjugate heat transfer and computational fluid dynamics to consider the conduction solids and the effects of wind speed and temperature in cold environments. The numerical analysis method of the surface heating element method was validated by comparing the experimental results of the heating coil method with the numerical analysis results (under the –30 ℃ conditions). The surface heating element method demonstrated significantly higher efficiency, ranging from 56.65–80.17%, depending on the conditions compared to the heating coil method. Moreover, even under extreme environmental conditions (–45 ℃), the surface heating element method satisfied anti-icing requirements. The surface heating element method is more efficient and economical than the heating coil method. However, proper heat flux calculation for environmental conditions is required to prevent excessive design.

fluidos no newtonianos, modelización numérica bidimensional, modelos reológicos, avalanchas de nieve, Ocean engineering, TC1501-1800, Hydraulic engineering, and TC1-978

La modelización numérica de fluidos no Newtonianos (relaves mineros, avalanchas de nieve, etc.) requiere la consideración de modelos reológicos específicos para calcular el esfuerzo cortante. El modelo de fricción de Voellmy es una de las teorías más populares, especialmente en el modelado de avalanchas de nieve. Recientemente, Bartelt propuso un modelo de cohesión para dar cuenta de esta propiedad física intrínseca de algunos fluidos. Sin embargo, la interpretación física del rango de valores del modelo de fricción-cohesión de Voellmy-Bartelt no ha sido suficientemente investigada, y este trabajo pretende llenar este vacío. Los resultados muestran que el modelo de Voellmy domina la dinámica de la avalancha y el modelo de cohesión permite la representación de colas largas, mientras que los parámetros de fricción y cohesión pueden variar dentro de un amplio rango. Adicionalmente, se propone la definición de un valor para el coeficiente de fricción turbulento basado en los mapas de usos del suelo del CORINE y el coeficiente de Manning para el mapeo de inundaciones.

corrientes de turbiedad, transporte de sedimentos, modelización hidrodinámica, Ocean engineering, TC1501-1800, Hydraulic engineering, and TC1-978

Se presenta el análisis hidrodinámico del embalse Amaluza, ubicado en el sur de Ecuador, mediante DELFT3D. Se ha dispuesto de información batimétrica en 30 secciones transversales a lo largo del embalse, que se ha registrado periódicamente desde 1983 hasta 2013. Para construir el modelo hidrodinámico, se ha utilizado una malla estructurada 3D y se muestra un resumen del proceso a seguir para garantizar la estabilidad numérica y precisión del modelo. Se ha llevado a cabo la calibración del modelo hidrodinámico en base a la curva hipsométrica del embalse y, asimismo, se ha simulado la corriente de turbiedad durante un episodio real registrado al inicio de puesta en servicio del embalse. La modelización numérica permite el análisis de diferentes escenarios asociados a distintas estrategias de gestión. Por ejemplo, se ha analizado el comportamiento de la llegada de sedimentos al embalse manteniendo los desagües de fondo cerrados y, en otro caso, con los desagües abiertos. Se aprecia que la apertura de los desagües de fondo mejora significativamente la capacidad de desalojar los sedimentos del embalse, lo que reduce su acumulación.

humedal construido, celda de combustible microbiana, agua residual real, eficiencia de tratamiento, bioelectricidad, Ocean engineering, TC1501-1800, Hydraulic engineering, and TC1-978

Se evaluó la eficiencia de un humedal construido acoplado con una celda de combustible microbiana (HC-CCM), a escala micropiloto, para tratar agua residual urbana real (ARU) y generar electricidad por acción de bacterias electroactivas que oxidan la materia orgánica. Para ello se construyó un humedal vertical de flujo ascendente al que se integraron 2 electrodos de grafito conectados a una resistencia externa de 1000 ohm. HC-CCM se alimentó continuamente con ARU sedimentada durante 4 meses. El tiempo de residencia hidráulico fue de 1.2 d. Semanalmente, se evaluó la calidad del ARU influente y del efluente tratado. El voltaje producido se registró cada 10 min. Las eficiencias de remoción medias logradas fueron: 95.8% turbiedad, 77.5% DQO, 75.7% sólidos suspendidos totales, 96.1% E. coli, 5.7% fósforo reactivo total y 18.3% amonio. HC-CCM produjo electricidad de forma continua, con rendimientos de hasta 30.5 W·h/kg DQO removida.

aforador de estrechamiento largo, canal, riego, hoja excel, arroz, Ocean engineering, TC1501-1800, Hydraulic engineering, and TC1-978

El arroz es regado por inundación manteniendo una altura de agua constante y alcanzando unos requerimientos de agua elevados. A la salida de la parcela hay un canal de desagüe cuyo control permitirá establecer prácticas para reducir el gran consumo de agua. Se ha diseñado un aforador de estrechamiento largo para cubrir el intervalo completo de caudales a aforar. Puesto que el canal de desagüe tiene una sección trapecial, la garganta del aforador será también trapecial para disminuir las pérdidas de carga. Un nuevo procedimiento se ha desarrollado en una hoja de cálculo Excel que permite diseñar directamente las dimensiones de la sección estrechada, talud de las paredes y anchura de la base, eligiendo previamente el límite modular, la altura del umbral y la longitud del estrechamiento más en concordancia con las características del canal. Los resultados demuestran la precisión y viabilidad del procedimiento.

flujo bifásico, banco de calibración, sonda aire-agua, fibra óptica, Ocean engineering, TC1501-1800, Hydraulic engineering, and TC1-978

A pesar de los avances significativos logrados en el estudio de los flujos bifásicos agua-aire, existen dudas acerca de la precisión de las campañas experimentales puesto que los equipos suelen obviar la fase de calibración. Las limitaciones inherentes a las técnicas de medición existentes han impulsado la presente investigación. El objetivo de este trabajo es profundizar en el conocimiento del funcionamiento de una sonda de fibra óptica de doble punta, ensayada en un banco de calibración con una fracción de vacío del 32.13%. Para alcanzar esta concentración se ha utilizado un caudal de agua Qw = 2.26 l/s y un caudal de aire Qa = 1.07 l/s. La evolución de las principales variables ha sido analizada en la dirección transversal del chorro, considerando diferentes secciones a distintas distancias respecto a la salida de la tobera. Estas variables incluyen: la fracción de vacío, la frecuencia de cambio de fase, la velocidad, y el diámetro medio de las burbujas de Sauter.

Ultrasonic testing, Machine learning, Feature extraction, Feature selection, Shapley additive explanation, Ocean engineering, TC1501-1800, Mechanical engineering and machinery, and TJ1-1570

Abstract Ultrasonic testing (UT) is increasingly combined with machine learning (ML) techniques for intelligently identifying damage. Extracting significant features from UT data is essential for efficient defect characterization. Moreover, the hidden physics behind ML is unexplained, reducing the generalization capability and versatility of ML methods in UT. In this paper, a generally applicable ML framework based on the model interpretation strategy is proposed to improve the detection accuracy and computational efficiency of UT. Firstly, multi-domain features are extracted from the UT signals with signal processing techniques to construct an initial feature space. Subsequently, a feature selection method based on model interpretable strategy (FS-MIS) is innovatively developed by integrating Shapley additive explanation (SHAP), filter method, embedded method and wrapper method. The most effective ML model and the optimal feature subset with better correlation to the target defects are determined self-adaptively. The proposed framework is validated by identifying and locating side-drilled holes (SDHs) with 0.5λ central distance and different depths. An ultrasonic array probe is adopted to acquire FMC datasets from several aluminum alloy specimens containing two SDHs by experiments. The optimal feature subset selected by FS-MIS is set as the input of the chosen ML model to train and predict the times of arrival (ToAs) of the scattered waves emitted by adjacent SDHs. The experimental results demonstrate that the relative errors of the predicted ToAs are all below 3.67% with an average error of 0.25%, significantly improving the time resolution of UT signals. On this basis, the predicted ToAs are assigned to the corresponding original signals for decoupling overlapped pulse-echoes and reconstructing high-resolution FMC datasets. The imaging resolution is enhanced to 0.5λ by implementing the total focusing method (TFM). The relative errors of hole depths and central distance are no more than 0.51% and 3.57%, respectively. Finally, the superior performance of the proposed FS-MIS is validated by comparing it with initial feature space and conventional dimensionality reduction techniques.

Spherical grinding head, Gradual contact arc length, Maximum undeformed chip thickness, Micro-grinding force, Ocean engineering, TC1501-1800, Mechanical engineering and machinery, and TJ1-1570

Abstract Micro-grinding with a spherical grinding head has been deemed an indispensable method in high-risk surgeries, such as neurosurgery and spine surgery, where bone grinding has long been plagued by the technical bottleneck of mechanical stress-induced crack damage. In response to this challenge, the ultrasound-assisted biological bone micro-grinding novel process with a spherical grinding head has been proposed by researchers. Force modeling is a prerequisite for process parameter determination in orthopedic surgery, and the difficulty in establishing and accurately predicting bone micro-grinding force prediction models is due to the geometric distribution of abrasive grains and the dynamic changes in geometry and kinematics during the cutting process. In addressing these critical needs and technical problems, the shape and protrusion heights of the wear particle of the spherical grinding head were first studied, and the gradual rule of the contact arc length under the action of high-speed rotating ultrasonic vibration was proposed. Second, the mathematical model of the maximum thickness of undeformed chips under ultrasonic vibration of the spherical grinding head was established. Results showed that ultrasonic vibration can reduce the maximum thickness of undeformed chips and increase the range of ductile and bone meal removals, revealing the mechanism of reducing grinding force. Further, the dynamic grinding behavior of different layers of abrasive particles under different instantaneous interaction states was studied. Finally, a prediction model of micro-grinding force was established in accordance with the relationship between grinding force and cutting depth, revealing the mechanism of micro-grinding force transfer under ultrasonic vibration. The theoretical model’s average deviations are 10.37% in x-axis direction, 6.85% in y-axis direction, and 7.81% in z-axis direction compared with the experimental results. This study provides theoretical guidance and technical support for clinical bone micro-grinding.

Shield machine, Tunneling parameters, Feature selection, Stratigraphic recognition, Ocean engineering, TC1501-1800, Mechanical engineering and machinery, and TJ1-1570

Abstract Shield machines are currently the main tool for underground tunnel construction. Due to the complexity and variability of the underground construction environment, it is necessary to accurately identify the ground in real-time during the tunnel construction process to match and adjust the tunnel parameters according to the geological conditions to ensure construction safety. Compared with the traditional method of stratum identification based on staged drilling sampling, the real-time stratum identification method based on construction data has the advantages of low cost and high precision. Due to the huge amount of sensor data of the ultra-large diameter mud-water balance shield machine, in order to balance the identification time and recognition accuracy of the formation, it is necessary to screen the multivariate data features collected by hundreds of sensors. In response to this problem, this paper proposes a voting-based feature extraction method (VFS), which integrates multiple feature extraction algorithms FSM, and the frequency of each feature in all feature extraction algorithms is the basis for voting. At the same time, in order to verify the wide applicability of the method, several commonly used classification models are used to train and test the obtained effective feature data, and the model accuracy and recognition time are used as evaluation indicators, and the classification with the best combination with VFS is obtained. The experimental results of shield machine data of 6 different geological structures show that the average accuracy of 13 features obtained by VFS combined with different classification algorithms is 91%; among them, the random forest model takes less time and has the highest recognition accuracy, reaching 93%, showing best compatibility with VFS. Therefore, the VFS algorithm proposed in this paper has high reliability and wide applicability for stratum identification in the process of tunnel construction, and can be matched with a variety of classifier algorithms. By combining 13 features selected from shield machine data features with random forest, the identification of the construction stratum environment of shield tunnels can be well realized, and further theoretical guidance for underground engineering construction can be provided.

Human digital twin, Human-cyber-physical system, Bidirectional long short-term memory, Convolutional neural network, Multimodal data, Ocean engineering, TC1501-1800, Mechanical engineering and machinery, and TJ1-1570

Abstract With the increasing attention to the state and role of people in intelligent manufacturing, there is a strong demand for human-cyber-physical systems (HCPS) that focus on human-robot interaction. The existing intelligent manufacturing system cannot satisfy efficient human-robot collaborative work. However, unlike machines equipped with sensors, human characteristic information is difficult to be perceived and digitized instantly. In view of the high complexity and uncertainty of the human body, this paper proposes a framework for building a human digital twin (HDT) model based on multimodal data and expounds on the key technologies. Data acquisition system is built to dynamically acquire and update the body state data and physiological data of the human body and realize the digital expression of multi-source heterogeneous human body information. A bidirectional long short-term memory and convolutional neural network (BiLSTM-CNN) based network is devised to fuse multimodal human data and extract the spatiotemporal features, and the human locomotion mode identification is taken as an application case. A series of optimization experiments are carried out to improve the performance of the proposed BiLSTM-CNN-based network model. The proposed model is compared with traditional locomotion mode identification models. The experimental results proved the superiority of the HDT framework for human locomotion mode identification.

Online correction system, Robot, Grinding, Weld seam, Laser vision sensor, Ocean engineering, TC1501-1800, Mechanical engineering and machinery, and TJ1-1570

Abstract The service cycle and dynamic performance of structural parts are affected by the weld grinding accuracy and surface consistency. Because of reasons such as assembly errors and thermal deformation, the actual track of the robot does not coincide with the theoretical track when the weld is ground offline, resulting in poor workpiece surface quality. Considering these problems, in this study, a vision sensing-based online correction system for robotic weld grinding was developed. The system mainly included three subsystems: weld feature extraction, grinding, and robot real-time control. The grinding equipment was first set as a substation for the robot using the WorkVisual software. The input/output (I/O) ports for communication between the robot and the grinding equipment were configured via the I/O mapping function to enable the robot to control the grinding equipment (start, stop, and speed control). Subsequently, the Ethernet KRL software package was used to write the data interaction structure to realize real-time communication between the robot and the laser vision system. To correct the measurement error caused by the bending deformation of the workpiece, we established a surface profile model of the base material in the weld area using a polynomial fitting algorithm to compensate for the measurement data. The corrected extracted weld width and height errors were reduced by 2.01% and 9.3%, respectively. Online weld seam extraction and correction experiments verified the effectiveness of the system’s correction function, and the system could control the grinding trajectory error within 0.2 mm. The reliability of the system was verified through actual weld grinding experiments. The roughness, Ra, could reach 0.504 µm and the average residual height was within 0.21 mm. In this study, we developed a vision sensing-based online correction system for robotic weld grinding with a good correction effect and high robustness.