1) To explore the impact on naval ship configurational
design of issues associated with crew manning numbers, function and
2) To identify key performance measures for successful crew performance in normal and extreme conditions.
3) To extend the ship evacuation software maritimeEXODUS to include additional non-emergency simulation capabilities.
4) To extend the ship design software so that it can provide a modelling environment that interactively accepts maritimeEXODUS simulation output for a range of crew evolutions.
5) To demonstrate a methodology for ship design that integrates ship configuration design with modelling of a range of crewing issues through PARAMARINE-SURFCON.
FSEG were responsible for objectives (2) and (3), UCL were responsible for objective (4) and both organisations were jointly responsible for objectives (1) and (5). By clicking on this link you will be connected to the UCL web pages associated with this project.
The partnership successfully achieved
all objectives, demonstrating the viability of the methodology and the
benefits that can be derived through its use. Key significantly novel
advances made in the project include:
The full project report presented to the EPSRC may be downloaded as a
pdf file. Download EPSRC project report
NOTE: This document will be made available after the project has been
assessed by the EPSRC.
|THE HPM METHODOLOGY||
A novel new discriminating and diagnostic methodology for assessing the HF performance of ship design has been developed which is systematic, transparent and repeatable. The method, known as the Human Performance Metric (HPM) allows the accurate and rapid assessment of HFs issues associated with vessel layout and crew operating procedures. The HPM works by systematically evaluating one layout design against another, whether two variants of the same design or two completely different ship designs. The analysis is performed using the maritimeEXODUS evacuation simulation software. The HPM involves specifying and defining a range of: Evaluation Scenarios, Performance Measures, Functional Groups and Weights. Each of these terms will be described.
The HPM requires the specification of a range of relevant Evaluation Scenarios (ES) against which the vessel will be tested. These scenarios are intended to define the scope of the challenges the vessel will be subjected to. In order to gauge vessel performance across a range of criteria, the ES are made up of both evacuation and Normal Operations (NOP) scenarios. The nature of the scenarios are dependent on the type of vessel. Relevant evacuation scenarios may include those required by MSC.1/Circ 1238 and include the IMO night and day scenarios or their naval equivalent. The NOP scenarios are dependent on the nature and class of vessel. For example, a cruise ship application may require the time to empty the cinema is minimised while a naval vessel may require watch changes to be completed within set period of time. Each ES is then simulated using the maritimeEXODUS software.
In addition to defining the ES, a range of Performance Measures (PM) must be defined that measure various aspects of personnel performance in undertaking the tasks associated with the ES. PM for passenger ship evacuation scenarios may include the time required to complete the assembly process while for a naval vessel NOP scenario, the total number of water tight doors (WTD) opened and closed may be relevant. The suitability of the vessel layout will be evaluated for fitness of purpose through some combination of the PM resulting from the execution of the ES. The PM values are determined from output for the ES produced by maritimeEXODUS.
As members of the ships complement may be involved in undertaking different tasks during a particular ES, the ships complement is divided into subgroups. Membership of each subgroup is determined by the nature of the tasks undertaken by the individuals in the particular ES, with each subgroup being made up of people undertaking a common set of tasks. These subgroups are labelled Functional Groups (FG). The introduction of FGs allows the analysis to focus on the performance of important subgroups of the crew whose contribution may swamp that of other FGs or be swamped by other FGs when considering the overall performance of the vessel. An example of a FG is the ‘damage control and fire fighting’ group which is a prime example of a FG used in circulation ES. In addition to the FGs defined by specific sub-populations, a special FG, identified as Ships Company, is included in all ES.
To complete the HPM, performance scores ai,j(PMk), for a particular design variant X associated with each PMk must be determined. The PM score (ai,j(PMk)) is simply its value derived from the execution of the maritimeEXODUS simulation software for each FGj within each ESi.
To allow a meaningful comparison between performance scores, each score is normalised, producing āi,j(PMk). The normalisation is performed using the largest performance score from the competing design variants X. Using this approach, all the HPM entries will be less than or equal to 1.0. The larger the performance score, the worse the performance of the FG for that particular PM.
An overall score can be determined for each FG representing the performance of the FG in the particular ES. This is calculated by taking a weighted sum of the normalised PM scores achieved by the FG across all the PMs. As not all PMs are considered of equal importance, a weighting is introduced to differentiate between various PMs. Thus each normalised score āi,j(PMk) will have a weight associated with it Ai,j,k, where subscript i refers to evaluation scenario ESi, the j subscript refers to the functional group FGj and the k subscript refers to the performance measure PMk. Thus the functional group score άi,j is given by
άi,j = (Ai,j,1 x āi,j(PM1)) + (Ai,j,2 x āi,j(PM2)) + - - - + (Ai,j,n x āi,j(PMn)) + - - -
An overall scenario score (SSi) can also be determined for each ESi representing the performance of all the FGs in the particular ES. This is calculated by introducing a FG weight Bi,j and taking a weighted sum of the FGj scores achieved in the ESi. Finally, an overall vessel performance can be determined for the design iteration X representing its performance across all the ESs. This is calculated by introducing an ES weight Ci and taking a weighted sum of the ES scores.
The HPM with scenario and design score along with the all the associated individual scores and weights are presented in the table below. The overall Vessel Performance VP, for design X can then be compared against the VP score for all other designs to determine which design produced the best overall performance. The matrix is also diagnostic in that it allows the identification of which measures contributed to the poor performance of a failed vessel design, or which PM could be improved in a winning design.
|MODIFICATIONS TO maritimeEXODUS||
The maritimeEXODUS software forms the core of the HF evaluation component of the system. This software was specifically designed to simulate evacuation scenarios and, as part of this project, its capabilities were extended to include the simulation of the NOP scenarios. This capability built on an existing feature known as the Itinerary List (IL). Using the IL it is possible to assign crew (and passengers) a list of tasks to perform. To accommodate the range of new scenarios that needed to be simulated to complete the HPM a range of new tasks were developed including:
In addition to these capabilities, a range of other modifications and additional software have been developed including:
|DEMONSTRATION APPLICATION OF HPM||
The following demonstration of the HPM concept involves evaluating the relative performance of two designs of a hypothetical naval vessel.
Naval evacuation scenarios;
The PMs for each variant were then determined and the final HPM constructed for each variant as shown below.
Variant 1 produces an overall Vessel Performance (VP) score of 523.7 while Variant 2 produces a VP score of 531.2. Thus we note that the overall performance of both variants is broadly similar, with Variant 1 producing a marginally better (1.4%) overall human factors performance according to the identified ES, PM and weights. Furthermore, we note that Variant 2 outperformed Variant 1 in most of the scenarios, however Variant 1 significantly outperformed Variant 2 in two NOPs scenarios. The worst performing scenario for Variant 1 is ‘Action Stations Evacuation’. As Variant 1 produces the better overall performance and produces significantly better NOPs performance it is considered the superior design. However, its performance may be improved by investigating why it did poorly in its worst performing ES.
To better understand why Variant 2 outperformed Variant 1 in the ‘Action Stations Evacuation’ scenario (ES3) and to identify potential areas in which Variant 1 can be further improved it is necessary to delve into the sub-components of the HPM (see below). Presented below are the PM scores for Variant 1 and 2 for ES3. We note that Variant 1 performed better than Variant 2 in five of the 18 PMs (G2, G5, M1, M14 and M16). Of these five PMs, four show at least 10% better performance than the respective Variant 2 PM, with M14 (most times a WT door was operated) and M16 (average number of doors used per person) returning 18% better performance. However, 12 of the PMs for Variant 1 returned poorer performance. Of these PMs nine returned values which were at least 10% worse than those in Variant 2. The poorest performance was achieved by G4 (average time spent in congestion) which returned 50% worse performance.
We note that for Variant 2, the overall average time spent in congestion (as measured by G4) was some 50% less than in Variant 1. This significant reduction in congestion results in Variant 2 being able to complete the scenario 11% quicker than Variant 1 (as measured by G3). Indeed, we note that while both vessels easily satisfy the international set evacuation time requirements (as measured by G3) the levels of congestion experienced exceed the international set limits in four locations (as measured by C1) and Variant 1 experiences the most severe congestion (as measured by C2). As the values for C1 and C2 are higher than the regulatory limits, neither vessel would be deemed to be acceptable. To address this issue and to improve the overall performance of Variant 1, further investigation is required to uncover the causes of the severe congestion.
Variant 1: Three Primary Congestion Regions in Actions Stations Evacuation
Exploring the areas of congestion in Variant 1 (using the population density graphical function available in maritimeEXODUS) suggested that a single additional ladder connecting 01 Deck with No 1 Deck between two of the severe congestion regions may alleviate some of the congestion by providing an additional means of vertical movement.
Suggested solution place additional ladder between 01_Deck and No_01_Deck.
Further analysis using maritimeEXODUS revealed that this simple modification eliminated two of the four congestion regions in the ‘Action Stations Evacuation’ scenario. With this modification in place the HPM was re-evaluated for the Modified Variant 1. The Modified Variant 1 now outperforms the original Variant 1 in each scenario and produces an overall VP which is 6% more efficient than the original Variant 1 design (see Table 7) and 8% more efficient than the Variant 2 design. We also find that the Modified Variant 1 design outperforms the Variant 2 design in all but the ‘Normal Day Cruising A’ evacuation scenario.
In summary, the HPM identified that the single passage variant produced marginally superior HF performance than the dual passageway variant. This demonstrates that the HPM methodology is discriminating. The HPM was also used to identify areas in which the HF performance of the single passageway variant could be further improved. Through adding a single ladder to the single passageway variant we improved its overall performance by 6% making the single passageway variant almost 10% better than the dual passageway variant. This demonstrates that the HPM methodology is diagnostic. Furthermore, the HPM methodology can routinely be applied to any given design and so is systematic, the logic process by which the decisions are made are transparent and another engineer using the methodology would arrive at the same conclusions and so the methodology is repeatable.
|PROJECT PUBLICATIONS AND PRESENTATIONS||
The following list of papers were produced by the project partners. Some of the publications and presentations are available in pdf format. Click on the link provided to download the publication where available or to view the powerpoint presentation.
Prof. Ed Galea
Fire Safety Engineering Group
University of Greenwich
Greenwich Maritime Campus
Old Royal Naval College
Queen Mary Building
Greenwich SE10 9LS
Tel: +44 (020)
Fax: +44(020) 8331 8925