watt systems technologies copyright © 2009, watt systems technologies all rights reserved...

Watt Systems TechnologiesCopyright © 2009, Watt Systems Technologies

All Rights Reserved

Traditional Systems Engineering

Kenneth A. Lloyd, Jr.

(Is REALLY Model Based Systems Engineering)

Objectives of this Presentation

Provide background context & research for SE?Raise awareness of models in SE practice.

SE Conops are models. SE Requirements are models. SE Validation and Verification are models. All SE Documents map to models.

Show Concepts are the foundation of models.Are Systems Models?

No, but you can model systems.Have some fun …

Background

“Scientists [and engineers] come to their particular problem withan accepted body of knowledge behind them, and on which they expect

to draw, without questioning the validity of each and every method,assumption, or set of facts that they use. If we all tried to work

everything out from first principles, or even insisted onunderstanding every piece of the puzzle in equal detail, none of usewould ever get anywhere. So to some degree we have to accept that

whatever has been acknowledged by the relevant community has beendone carefully and correctly, and can be relied on … But the

process is far from perfect, and once in a while we are surprised todiscover that a piece of knowledge we had long taken for granted is

questionable or even wrong.”

-Duncan J. Watts, fromDuncan J. Watts, from““Six Degrees: The Science of aSix Degrees: The Science of aConnected Age” [p. 132]Connected Age” [p. 132]

Background

Experts notice features and meaningful patterns of information that are not noticed by novices.

Experts have acquired a great deal of content knowledge that is organized in ways that reflect a deep understanding of their subject matter.

Experts’ knowledge cannot be reduced to sets of isolated facts or propositions but, instead, reflects contexts of applicability: that is, the knowledge is “conditionalized” on a set of circumstances.

Experts are able to flexibly retrieve important aspects of their knowledge with little attentional effort.

Though experts know their disciplines thoroughly, this does not guarantee that they are able to teach others.

Experts have varying levels of flexibility in their approach to new situations.

John D. Bransford, Ann L. Brown, and Rodney R. Cocking (eds.), How Experts Differ from Novices

4 Major Concerns of SE

Enterprise aspectsTechnical aspects Project aspectsAgreement aspects

Our focus

Brief

Enterprise Aspects

Models – Steve Lehar

Phenomenon

Model

Courtesy: Steve Lehar, PhD – Cognitive Science, Boston University

Concept

Concepts do not need, nor do they havethe same “topology” as reality.

They have maps.

Models – Roger Penrose

PhenomenonConceptual

Model

Roger Penrose – Road to Reality

The Chasm – The Problem Domain

Courtesy: Steve Lehar, PhD – Cognitive Science, Boston University

Minimal Model System

errormodeldata

A statement of what you believe you know, and what you don’t

Real worldPhenomenon

A Hypothesis orTheorem*

**Idealized at equilibrium

In Mathematical Language

MmgfF ,:

F is called a functor

Carnegie-Mellon Models

Carnegie-Mellon UniversityA System of Model Interaction

Related to Phenomenon

Familiar Ground - The SE ‘V’

Evolutionary ‘V’

Background - The SE ‘V’

Models

TheManWhoMistookHis BrainFor HisMind

Models

INCOSE Handbook 3.1 p. 2.4Aussi, ceci n’est pas un modéle

Conceptual Hierarchy

Conceptual

Language

Taxonomy

Ontology

M3 Meta-metamodel

M2 Metamodel

M1 Model

M0 Object

Hig

her A

bstractio

n

Alex Stepanov’s Concept Model

Maps to Models

Conceptual

Language

Taxonomy

Ontology

M3 Meta-metamodel

M2 Metamodel

M1 Model

M0 Object

Each level has elements of self-similarity – but not equality

errormodeldata Petri netsUML, SysML andTextual Documents

Technical Aspects

Requirements definition,Requirements analysis, Architectural design, Implementation, Integration,Verification, Transition, Validation, Operation, Maintenance, and Disposal

Focus

Focus

Focus

Zia - A Real-world Example

Concept of Operations

Zia goes here

Overview

Overview (excerpt)“Effective management and stewardship of the nuclear weapons stockpileinto the future requires the ability to accurately assess the behavior of the weapons in order to ensure robust and reliable performance while maintaining the testing moratorium. These accurate assessments drive the requirements for predictive capability in weapons science, including a fine-scale numerical resolution and advanced models for physics and material behavior.” – pg. 5

Model?Model?

Models?

?

Models – Steve Lehar Redux

Phenomenon as

Measureable,MeaningfulData:

Requirements

Model

Courtesy: Steve Lehar, PhD – Cognitive Science, Boston University

Concept

Requirements do not need, nor do they havethe same “topology” as reality.They have maps to models.

What doesthis requirementmean?

Zia’s High Level Reqs.

Mapping Information to Models

Agents, spiders and crawlers … Oh, my!

What does it all mean?

Contact Info

Kenneth A. Lloyd, Jr.Director, Systems ScienceWatt Systems Technologies Inc.Albuquerque, NM 87114 USAkenneth.lloyd@wattsys.com