105 results about "Stowage" patented technology

This invention provides a comprehensive maritime shipbroking platform uniting digital twin modeling, AI-driven cargo allocation, blockchain-based contract management, predictive maintenance (AR / VR), route optimization, real-time tracking, and single-window compliance. The digital twin engine continuously simulates vessel performance, enabling data-driven decisions on stowage, scheduling, and maintenance. A cargo-freight matching module optimally allocates shipments, factoring in market rates, vessel metrics, and port congestion. Blockchain-secured smart contracts automate negotiations, ensuring transparency and tamper-proof enforcement. A predictive maintenance system applies advanced analytics to diagnose technical issues early, while the route optimization engine finds cost-effective, emission-compliant routes. Real-time tracking gives stakeholders constant visibility, and the single-window interface integrates Electronic Bill of Lading processes, satisfying IMO and IG P&I standards. Additionally, a dynamic vessel ranking system incorporates SIRE, RightShip, PSC, and user feedback for safer, more efficient chartering decisions. The invention addresses day-to-day operational challenges in maritime logistics, elevating efficiency and compliance.

The invention provides a container shipping stowage method and system based on a multi-stage optimization algorithm, is applied to the technical field of operational research and port logistics, and decomposes a complex stowage process into a plurality of optimization stages based on a four-stage mixed integer programming method. The method comprises the following steps: firstly splicing 20-foot boxes into 40-foot equivalent boxes, quickly locking a shipping space by taking the minimum box area-ship-shellfish connection number and weight deviation as targets, then eliminating vertical overweight and transverse unbalance layer by layer, and finally finely adjusting the shipping space through local neighborhood search, thereby reducing the box turnover rate and improving the dispatching efficiency. Therefore, higher efficiency, lower conflict rate and better process matching degree of container space distribution are realized, the adaptability and efficiency of actual wharf operation are remarkably improved while the safety of a ship structure is guaranteed, and intelligent, systematized and efficient development of a port operation system is promoted.

The present disclosure provides a tray table assembly including a pouch configured to temporarily stow travel essentials during flight. The pouch is removably attached to the back of the tray table by way of a plurality of removable fasteners. The pouch includes inner and outer layers forming an interior space therebetween accessible through a top opening that may be zippered or otherwise closeable. In some embodiments, the pouch is constructed from soft material such as neoprene rubber, and at least the outer layer is made from mesh or translucent material such that the contents are visible to the passenger, so they are not forgotten and left behind.

The invention provides a floating dock lightering analysis method which comprises the steps that finite element models of a ship to be lighted and a bearing beam are established in finite element analysis software, the bearing beam is arranged on a bearing trolley and can move along with the bearing trolley, and a plurality of cushion blocks used for supporting the ship are arranged on the bearing beam; calculating the reaction force of each cushion block, and arranging the reaction force to form a reaction force distribution diagram; judging whether the bearing beam with the deformation degree exceeding the allowable standard exists or not; in the lightering process, a plurality of typical stowage working conditions are selected, overall stress analysis is conducted on the floating dock under the typical stowage working conditions, and a floating dock stowage scheme is determined; a finite element model of the floating dock is established, a plurality of typical stress working conditions are selected in the lightering process, and finite element analysis is conducted on stress distribution and deformation of the floating dock structure under the typical stress working conditions. According to the technical scheme, the calculation efficiency and simulation precision of the floating dock lightering process can be effectively improved, and the safety of the ship during floating dock lightering is better ensured.

The invention relates to the technical field of intelligent logistics and operation planning optimization, and discloses an import and export multimodal transport intelligent stowage service method based on a hybrid planning algorithm, which comprises the following steps: establishing an intermodal transport node operation impact database and an intermodal transport network diagram, and defining a node stacking operation state set; according to the force transmission attribute of the corner column of the container, the discrete stacking hierarchy is mapped into vertical pre-pressure, and the node working condition inherent frequency of the container-cargo combination is calculated through a pre-pressure and rigidity correlation model; in combination with node pulse dominant frequency data, constructing a response gain index including resonance interval intensity and parameter fluctuation sensitivity; and establishing a multimodal transport stowage optimization model, bringing the index into a target function, and carrying out collaborative solution on a cargo loading layout, a transport link and a node stacking level. Resonance risks caused by discrete stacking and lateral impact coupling can be effectively recognized and avoided, and a stowage scheme with high structural safety is output.

The invention discloses a large language model multi-agent end-to-end stowage method considering outbound equipment collaborative scheduling, which comprises the following steps: acquiring description data of a stowage task, and decomposing the stowage task into sub-tasks of multiple stages based on the description data; aiming at the first subtask, based on the description data of the first subtask, constructing a first model by utilizing a modeling agent, and generating a first code for solving the first model through a model code agent; aiming at the second subtask, based on the description data of the second subtask, constructing a second model by utilizing the heuristic intelligent agent, and generating a second code for solving the second model through the heuristic code intelligent agent; matching target codes from the first codes and the second codes according to the types of the sub-tasks, and executing the target codes according to the sequence of the sub-tasks to obtain a final container stowage plan. The method can meet the reality and feasibility and completely meet all complex requirements.

A row of docking stations to stow containers or trolleys is provided along at least one side of a van cargo storage area and a corridor for loading and unloading containers or trolleys individually or in groups from the rear of the van is provided. Preferably, the docking stations are automated. Interference with the storage and removal of containers or trolleys by the wheel wells of the vans or other vehicles is eliminated. Motorized mechanisms capture and lift the containers or trolleys above the level of the wheel wells for stowage in the docking stations to maximize the available storage area beyond that available on the floor of the cargo area. Individual containers or trolleys may be maintained in docking stations until needed.

The invention provides a ship loading method based on a multi-intelligent optimization algorithm, and relates to the technical field of shipping loading optimization, and the method comprises the following steps: S1, stowage request receiving and data preprocessing: receiving a stowage request and carrying out data processing on ship parameters, cargo information and loading rules; s2, deck virtual area division and functional area mapping: dynamically dividing a deck into a plurality of functional sub-areas according to loading rules and cargo attributes; s3, region-level multi-algorithm collaborative loading: for each sub-region, dynamically matching based on region characteristics and cooperatively executing at least two different types of intelligent optimization algorithms to carry out cargo loading; s4, performing global scheme verification and dynamic fine adjustment, including summarizing loading schemes of each sub-region, and performing global weight balance and security channel connectivity verification; and S5, outputting and visualizing a loading result. According to the method, multiple constraint conditions can be automatically processed, the optimization strategy is dynamically matched, and global optimization is realized.

The invention discloses an emergency material vehicle cargo matching and stowage optimization method and device based on two-stage mixed taboo search and a medium, and the method comprises the steps: building a cargo stowage and vehicle path comprehensive transportation model, and the composition factors in the comprehensive transportation model comprise loading space, loading capacity and road section traffic capacity; inputting an emergency material transportation task set in the planned time period, wherein information contained in each transportation task comprises a starting place, a destination place, a cargo quantity, a cargo volume and a cargo weight of each transportation task; constructing an alternative path set by adopting a genetic algorithm according to the comprehensive transportation model and the emergency material transportation task; and in consideration of transport tasks, the number of vehicles and transport capacity constraint conditions, a tabu search algorithm is adopted to solve an emergency material transport optimization scheduling problem, and an optimal scheduling scheme is selected from the alternative path set. The cost is reduced, the logistics efficiency is improved, and a feasible solution is provided for the cargo transportation stowage problem.

The invention relates to the technical field of freight shipment, in particular to a shipment method based on a dynamic stowage mode, which comprises the following steps: analyzing ship shipment data and storage yard equipment distribution conditions to obtain shipment operation sequences under different shipment operation lines, and determining the shipment data under the same shore bridge as shipment single-group data; analyzing the shipment single group of data to obtain an operation sequence of the containers with the same container attribute; solving container truck requirements of different operation lines of the whole ship by using a recursive algorithm, and solving container discharging at a storage yard side by using a Monte Carlo tree search algorithm according to attribute operation requirements of a shore side container; the storage yard position suitable for container discharging is dynamically planned based on the distribution condition of storage yard side equipment and the storage yard sequence set by wharf operators, an adaptive shipping strategy is selected based on an algorithm result for shipping, and the problems that in the prior art, shipping efficiency is low, flexibility is poor, and safety cannot be guaranteed are solved.

The application discloses a port management method, system and equipment based on a digital intelligent algorithm, belongs to the field of smart ports, and comprises the following steps: collecting cargo information, ship information and vehicle information and performing pretreatment; performing intelligent berth planning according to the pretreated ship information to obtain berth information, then performing intelligent stowage planning according to the pretreated cargo information, the pretreated vehicle information and the berth information to obtain stowage information; collecting port storage information, combining the stowage information with the port storage information to perform intelligent stacking planning to obtain stacking information; performing intelligent site selection according to the berth information, the stowage information and the stacking information to obtain site selection parameters and site selection tasks, and automatically sending containers according to the site selection parameters and the site selection tasks to realize real-time scheduling of the port. The application can solve the problem that the prior art cannot realize dynamic management of the port.

The utility model discloses a logistics vehicle cargo loading and filling device which comprises a box body, a plurality of bottom plates are arranged in the box body, partition plates are arranged in sliding grooves, a plurality of limiting holes are formed in the upper portions of the bottom plates, limiting plates are fixedly installed below the partition plates, grooves are formed in the limiting plates, and bearing guide rails are arranged in the box body. A plurality of object supporting plates are arranged in the bearing guide rail, hinges are fixedly installed between the object supporting plates, the fixing shaft comprises a movable installation part pulley and a fixed installation part fixing ring, and the movable installation part pulley is arranged in the bearing guide rail in a sliding and sleeved mode. By means of the structure, a partition plate independent locking mechanism prevents displacement in the transportation process, the collision damage risk of goods is reduced, stacked goods are prevented from collapsing through modular partition, the three-section type folding hinge structure enables the thickness of the folded shelf plate to be greatly reduced, and the shelf plate does not occupy the effective loading space in the folding state.

The intelligent twist lock for the container ship comprises a lock body master control box, an upper lock head driving box and a lower lock head driving box are arranged on the upper portion and the lower portion of the lock body master control box respectively, an upper lock head is arranged on the top of the upper lock head driving box in a sliding mode, and a lower lock head is arranged at the bottom of the lower lock head driving box in a sliding mode; an upper lock head driving assembly is arranged in the upper lock head driving box, and a lower lock head driving assembly is arranged in the lower lock head driving box. A lock body information chip convenient for a ship remote control platform to remotely operate the twist lock is arranged on the front side of the upper lock head driving box; the lock body information chip and the control module are additionally arranged on the twist lock, and the twist lock is in communication connection with the ship remote control platform, so that key data basis and equipment support are provided for intelligent stowage and yard automatic management of the container ship; the driving motor is matched with the precise spiral lifting and rotating mechanism, so that the whole process automation of locking and unlocking of the twist lock is realized, the working efficiency is greatly improved, and the labor intensity is reduced.

The invention discloses an intelligent management system for international trade export business. The intelligent management system comprises a system setting module, an external consultation module, a service demand module, an intelligent cabinet arrangement module and an intelligent report module, and the system setting module is used for setting and defining corresponding related data in the business demand module, the intelligent cabinet arrangement module and the intelligent report module and association relationships among the related data. The intelligent management system is based on the push-and-pull order technology, achieves one-stop management of the whole foreign trade process from clients to purchasing to shipping to final financial settlement and the like, achieves rapid information generation of the whole process, reduces repeated information input by users, and improves the accuracy of information input. Meanwhile, manual operation is simplified through an intelligent algorithm, the problem that delivery to customers is not timely due to manual operation omission is avoided, and the working efficiency of employees is improved.

The invention discloses a port container shipment cabin position monitoring method, and belongs to the technical field of container shipment automation, and the method comprises the following steps: outputting a stowage chart; coordinates of all points on the ship in the space rectangular coordinate system are obtained; the corresponding containers are clamped, and the containers are transferred according to the coordinates, obtained through last adjustment and updating, of the corresponding shipping spaces of the containers; through first position adjustment, the container corresponds to the position of the corresponding cabin; after the position of the container is stable, the height of the container is gradually reduced. Through laser radar multi-source scanning and three-dimensional digital twinborn body comparison, real-time mapping of a ship and port coordinate system is established, high-precision coincidence of a container projection position and a target shipping space is realized in combination with identification of a visual system on shipping space corners, accurate determination of a container placement position is realized, and high-precision positioning of the container is realized. Therefore, the positioning and position adjusting time in the container shipping process is shortened, and the shipping efficiency is improved.

The invention discloses an ocean container transport ship design system and method based on digital twinning, and belongs to the technical field of ship engineering and digital twinning. The method aims at solving the technical problem that traditional finite element analysis cannot provide real-time feedback due to massive working condition combinations in the design process of the ocean container transport ship. The system and the method comprise the following steps: constructing a standardized topological domain for unifying different ship type variants; a high-fidelity full-component stress tensor sample set under the working condition of a small number of anchor points is calculated in an off-line mode; performing orthogonal decomposition on the sample set, and extracting a group of orthogonal stress bases carrying dimensional information; in the design interaction stage, the system predicts a dimensionless modal coefficient through a pre-training model according to design parameters such as a hull geometric variant, a stowage scheme and a sea condition input by a designer, performs linear weighted stacking on the dimensionless modal coefficient and a stress base, reconstructs a full-field stress tensor of a hull structure in real time, and generates a visual evaluation result.

The invention relates to the technical field of cargo stacking, in particular to a bulk cargo stacking method based on an inclined gradient cabin stacking method, according to the stacking method, through a specific inclined gradient cabin stacking mode, a trapezoidal structure with the wide bottom and the narrow top is formed, the center of gravity of cargoes is effectively lowered, bag collapse caused by center-of-gravity shift is prevented, and potential safety hazards such as cargo falling are reduced. And life health of workers is guaranteed. In the actual bulk cargo loading and unloading operation, a traditional stacking mode is prone to causing accidents due to unstable cargo stacking, however, the stacking structure is optimized, the operation safety is greatly improved, the cargo stacking process is simplified, the shipping time is shortened, and the whole operation process is smoother and more efficient.

The invention discloses a flight stowage release management method based on data prediction, which belongs to a flight load quantity fine management method, and comprises the following steps of: judging whether a current flight is overloaded or not through a unique formula algorithm, and calculating whether the current flight is overloaded or not by taking a runway direction, a cargo set and the standard weight of passengers as a basis; and through a way of predicting the runway direction, the luggage weight and the loadable weight data, the whole process integration of'release-stowage-monitoring 'is realized, the passenger and freight sales space of an airline company is released to the greatest extent, and more intelligent auxiliary decision-making functions are realized.

The application provides a logistics resource allocation and loading method and system, an electronic device and a storage medium. The method comprises the following steps: acquiring basic data information and shipping task information; constructing a logistics resource association model according to the basic data information; inputting the shipping task information into the logistics resource association model to obtain an association result of a shipping task corresponding to a finished product; and performing direct shipping determination based on the association result. If the determination result is direct shipping, the finished product is classified into a first set; if the determination result is not direct shipping, the finished product is classified into a second set. The shipping vehicle state information, the first set and / or the second set are used to determine a collaborative execution scheme to perform logistics resource allocation and loading. The method realizes collaborative decision of logistics resources and shipping tasks, effectively reduces waste of reverse transportation resources, loading waiting and shipping delay, and improves the on-site executability of a shipping plan.

The utility model provides a kind of instrument and equipment retraction device applied to ship stern, it includes slide and sea chest, slide extends to ship stern, one end of slide is equipped with winch, winch is wound with pull rope, the other end of slide is set in the opening to the outside of ship, slide is set with opening as lowest point to be inclined downward, sea chest is open structure, separable instrument and equipment are fixedly installed in sea chest, the outer end of pull rope is fixedly connected with sea chest;When needing to put instrument and equipment into sea to work, winch is used to release pull rope to specific length, so that sea chest can slide into ship stern and fall into sea in slide, so that sea chest is flooded, instrument and equipment are also located in sea, at this time, instrument and equipment are separated from sea chest;When instrument and equipment located in sea to work are recycled to ship, instrument and equipment are fixed in sea chest in sea, winch is used to wind up pull rope, to recycle sea chest to ship;The utility model belongs to the technical field of ocean engineering equipment.

The invention relates to a package including a bottom and panels including a lid, the package being foldable between a use configuration defining a stowage volume, and in which the lid is capable of sealing the stowage volume; a flat configuration; the package including, in the flat configuration of the package, anchors between the bottom and at least one of the panels in a position folded down against the bottom, each anchor exerting a force for holding one of the panels in its position folded down against the bottom.

This invention belongs to the field of cargo stowage technology and provides an AI-based self-learning system for general cargo stowage operations. The system includes: simulating the loading of general cargo using digital twin and AI technologies, outputting several simulated loading schemes; acquiring data on the loading location, unloading sequence, weight, additional unloaded cargo quantity, and cargo hold weight distribution for each scheme; establishing an unloading status analysis model based on the loading location, unloading sequence, and additional unloaded cargo quantity to generate a comprehensive score for unloading rationality; generating a stacking safety risk score based on the loading location and weight; establishing a balance analysis model based on the weight distribution data to generate a balance risk score; and generating the optimal simulated loading scheme by combining the above scores, thereby determining the stowage operation scheme. This invention, through multi-dimensional risk quantification and a self-learning mechanism, achieves intelligent optimization of general cargo stowage schemes, improving unloading efficiency, cargo safety, and ship stability.

Transporter load management system (3), comprising: a generally rectangular transporter cargo space (7) with a floor (9) and opposite side walls (17, 19) which can accommodate a plurality of containers (23); a rear opening (21) allowing access to and exit from the loading space (7); and at least one stowage mechanism (27) arranged next to one of the side walls (17, 19) and suitable for picking up a selected container (23) from the loading space floor (9) and pulling the selected container (23) laterally towards a side wall into one of a plurality of stowed positions next to the side wall, stowing the selected container next to a side wall of the loading space (7) at a distance above the floor (9) and returning the selected container laterally from the stowed position to the loading space floor (9).

The application discloses a container ship stowage method based on an improved ant colony algorithm under self-adaption and multiple targets, and comprises the following steps: first, parameter initialization, a multiple-target ant colony model is constructed, the number of ants, the maximum number of iterations, the pheromone concentration is initialized, the pheromone evaporation coefficient, the pheromone importance coefficient and the heuristic factor coefficient are set, according to the multiple-target characteristics of the container ship stowage problem, a multiple-target weight coefficient vector is constructed, and on the multiple-target optimization level, the edge weight dynamically fuses the box turning penalty (P), the cross-pile area moving cost (C) and the weight deviation (W), and the adaptive weight distribution strategy (such as fuzzy logic dynamic adjustment omega 1-omega 3) is combined, so that the algorithm can flexibly balance the efficiency and safety under complex working conditions, and the multiple-target priorities are balanced through the adaptive weight distribution.

The invention relates to a freight rate calculation method and device for air freight. The freight rate calculation method for air freight comprises the following steps: acquiring freight rate rule information to generate freight rate calculation logic; in response to the received booking information, calculating an estimated freight rate in real time based on a freight rate calculation logic, and determining whether to batch the cabins based on interaction of the estimated freight rate and the booking information; in response to determining the batch, generating order making information to calculate an actual freight rate based on the order making information, and generating freight order information based on the order making information and the actual freight rate; obtaining international aviation cargo booking order CBA information based on the booking information, and generating stowage management information based on the CBA information and the waybill information; and in response to a stowage exception in the stowage management information, generating rebooking information based on the stowage exception, and updating the booking information based on the rebooking information to calculate the latest freight rate.

The invention provides a multi-mass-center working condition stowage verification method and device, electronic equipment and a storage medium. According to the method, virtual stowage adjustment of mass blocks is continuously performed on each stowage area in a simulated container of a target test truck through a constructed mass center coordinate calculation model according to a set target mass center and mass requirements, and mass block stowage can be accurately performed on each stowage area in the simulated container of the target test truck. Besides, according to the method, the theoretical centroid after stowage is verified through the set target centroid and mass and the constructed centroid coordinate calculation model, so that the theoretical centroid can be continuously close to the set target centroid. Meanwhile, the stowage verification process is realized by simulating the container, more verification working conditions can be realized, the comprehensiveness and feasibility of verification schemes of different centroid working conditions are greatly improved, and more comprehensive and objective reference basis is provided for design and development of trucks.

The invention relates to the technical field of international freight agency, in particular to an international freight agency cargo stowage path optimization method, which comprises the following steps: firstly, collecting and preprocessing multi-source heterogeneous data, and constructing a comprehensive database comprising cargo characteristics, transportation tools, road condition policies and cost effectiveness; on the basis of an analytic hierarchy process-genetic hybrid algorithm, the cargo stowage priority is determined, intelligent stowage is completed, and accurate matching of the weight, the size, the characteristics and the shipping space of the transportation tool is achieved; then combining real-time dynamic data, adopting an improved Dijkstra algorithm to carry out initial path planning, and dynamically adjusting the path through a rolling window iteration mechanism; and finally, verifying the feasibility of the scheme through a cross-modal information interaction correction module, and generating an optimal stowage path combination. According to the method, collaborative optimization of stowage and paths is realized, the dynamic adaptability and the resource utilization rate are improved, the transportation cost is reduced, the transportation period is shortened, and the method is suitable for complex international freight scenes such as multimodal transportation and cross-border transportation.

The invention discloses a freight vehicle visual management method and a storage medium, and relates to the technical field of freight management, and the method comprises the steps: building a digital twin model of vehicle loading, and carrying out the real-time mapping of a carriage structure, a cargo position and the load condition of each region; a weight sensor, bar code scanning and image recognition data are fused, the comprehensive weight of each cargo is calculated by adopting weighted average, and the cargo placement position is dynamically optimized by utilizing a virtual stowage algorithm on the premise of integrating vehicle structure limitation and non-overlapping constraint, so that the overall center of gravity is close to a predetermined target as much as possible; the method comprises the following steps: constructing a vehicle internal space topology model by using a graph neural network, taking each cargo as a node, extracting spatial features through nonlinear mapping, inputting an aggregated feature sequence into a long-short-term memory network, performing time sequence analysis on historical loading data, predicting dynamic change of the gravity center in a few minutes in the future, and determining the dynamic change of the gravity center in the long-short-term memory network. And the conversion from static monitoring to dynamic early warning is realized.

An automated lashing bar (ALB) (100,100a,100b), a lashing robot (200,200a,200b,200c), and a system and a method for automated lashing of containers onboard a ship are provided. Each ALB, includes: a bottom end, a top end, and a middle portion. The bottom end of the ALB is configured to pivot about lashing points (303) located on lashing bridges (300), whilst the top end is configured to engage into a corner casting (502) located on a container for lashing. The middle portion of the ALB has a threaded joint for rotatably tensioning or loosening the container to the respective lashing points. The top ends of the ALBs are placed at stowage hardpoints (304) located on the lashing bridges, a robotic canopy or a stalk. The lashing robot has wheels, legs or feet to allow it to travel on a hull of the ship, on the robotic canopy or on surfaces of containers.