Frusta Limosus

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Engineering education has rightly emphasized the study of the quantifiable aspects of design. In decades past this took the form of discoveries the mathematical relations that governed physics of engineering interest, i.e: structural mechanics, hydrodynamics etc.

Our interest in these areas continues, and much engineering research is devoted to continuously improving these models, whether by carrying them to higher accuracy or by extending them to previously intractable applications, e.g. mixed flows.

At the same time, however, it is increasingly the case that engineering "failures" are due not to errors in the physics, but due to failures in human decision making, operation, or program management. This has long been true, but engineers were able to say that these subjects were outside of their bailiwick, and could lay the blame at the feet of some distant group of managers. Today, however, we are growing in understanding engineering to take place within a super-system framework. That in turn means that we can not draw a line between engineering and decision making.

And today's discussion of design tools as decision aids exemplifies this understanding. We still, however, have a mental distinction between the quantifiable physics-based aspects of engineering, and these other and currently non quantifiable components. The fact that some of these aspects are currently non quantifiable suggests to me that they are aspects we ought to devote some resources to. We already have excellent tools for predicting a broad variety of hydrodynamic properties. We have a much sparser tool set for predicting human performance.

When was the last time a ship went down do to hydrodynamic failure? When was the last time one went down due to human error? In recognition of this, UNO is proposing an institute to advance research into the muddy, intractable, currently non quantifiable aspects of naval architecture, the Frusta Limosus Center. The Frusta Limosus Center tackles problems that are outside the domain of business as usual. These we problems that have been characterized as Grand Challenges, or wicked problems.

The following is a brief - and for from comprehensive – list of such topic areas.

  • Formulae for innovation
  • Measures of Human Performance
  • Formulae for ship aesthetics
  • Quantitative technology forecasting
  • Quantitative assessment of ship arrangements
  • Design for sustainability
  • Design for survivability

I have opined that the Frusta Limosus are overlooked simply because they are "too hard." Therefore, if I am going to argue that they _should_ be modeled then it behooves me to show that they _can_ be modeled. The paragraphs that follow offer a list of potential Measures of Performance (MOPs) that could be used to render the Frusta Limosus quantifiable.

Human Factors Engineering: A metric for the HFE “goodness” of ship arrangements may be harvestable from the objective functions used in the Intelligent Ship Arrangement (ISA) projects.

Human Throttle Interaction: Using the UNO time-domain unsteady planing model it is possible to calculate craft accelerations, with taking into account a non-steady thrust force.

A non-steady thrust force may be considered a very simple model of a human driver non-steady throttle profile.

I suggest as a first attempt, calculating a few limiting cases. Of course the first limiting case is “set it and forget it” a case in which the throttle is fixed. This is not exactly the same as a fixe thrust, so it may be necessary to determine the extent to which “fixed thrust” fails as a model of “fixed throttle.”

The other extreme value is to assume a perfect thrust variation, such that there is zero acceleration in the direction of travel. (There will still be vertical accelerations.) This case is mathematically simple, in that it requires calculating the unbalanced x-force at each time step, and then modifying the thrust to eliminate this imbalance.

Of course, this condition is unrealistic because it implies instantaneous throttle response and / oir instantaneous sensation. In light of this an obvious follow-on would be to include a time lag between the imbalance and the change of thrust. Other modifications are also possible.

In either case the output of interest would include the motions of the craft, and magnitude of the thrust excursions.

Acquisition Methodology: The acquisition methodology employed affects the ship. In many cases the effect that it has is to modify the ship: single-mission ships become multi-mission, high-speed ships become moderate speed, and so forth. Indeed, even Hollywood recognizes this fact, as dramatized in The Pentagon Wars.

The result of this effect is that the ship conceived during AoA becomes a different ship by IOC.

And this evolution is never without some cost, upon either capability, characteristics, or economics.

This type of Frusta Limosus – the acquisition system effect – can in fact be described as a transfer function: Ships that come in with characteristic “A” will leave with characteristic “B”. The act of describing this as a transfer function also describes the tool for tackling it: Armed with data on past AoA selection, and comparing their characteristics with those of the eventually-procured system, it would be interesting to try to regress a curve fit model of the transformation. I imagine that the variables of interest might include:

  • Global tension at the time
  • National economics at the time
  • Magnitude of the considered project
  • TBD

Finally, while I purposely used the word “regression” above, I suspect that a neural network will be a better tool for developing the model of the transformation function, because I believe the effect of the acquisition system to be highly non-linear.

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